Science blogging in theory and practice

Correlation between reference managers and the WoS

2011-12-30T21:28:00.000-08:00

Even though web citations have been a part of our lives for several years now, the correlation between "traditional" citations and web resources like Mendeley, CiteULike, blog networks, etc. hasn't been thoroughly studied yet, and any new research in the field is very interesting (to me, anyway).

The new paper was published at Scientometrics by Li, Thelwall (still one of my dissertation advisors) and Giustini. They focused on the correlation between user count - the number of users who save a particular paper - and WoS and Google Scholar citations.

The researchers extracted from WoS all the Nature and Science research articles that were published in 2007 and their references. They ended up with 793 Nature and 820 Science articles, or 1,613 articles overall (not including references, of course). Then, they searched CiteULike for those articles' titles and number of citations, as well as for their user count in Mendeley. They also collected the same data from Google Scholar. It's important to note that Mendeley had 32.9 million articles indexed while CiteULike had only 3.5 at the time of the study.

Google Scholar's mean and median number of citations were higher than in WoS (not surprising; If you want better citation numbers, always use GS). They found that despite Mendeley being "younger" than CiteULike (launched in 2004 and 2008 respectively), CiteULike had only about two-thirds of the sample articles saved, while Mendeley had about 92%.

Spearman correlations between citations in GS and WoS were high in this research (0.957 for Nature and 0.931 for Science). The correlations between Mendeley's user count and the citations in GS and WoS were also rather good (0.559 and o.592 for WoS and GS respectively for Nature, 0.540 and 0.603 for Science). CiteULike had far weaker correlations: 0.366 with WoS and 0.396 with GS for Nature, 0.304 with WoS and 0.381 with GS for Science.

Limitations

The authors remind us that correlation isn't causation, saying they can't conclude a casual relationship based on correlations between two data sources. Therefore, it can't be determined for sure whether there is a connection between a high user count and a high number of citations. Only Nature and Science were studied, so it can very well be that the results aren't true for other journals. Also, group-saved and single-user saved references were given the same weight. The number of saved references in Mendeley and CiteULike is much smaller than in the WoS counts and therefore the results might be less reliable.

The authors speculate that user count may represent a more accurate scientific impact of articles, and take note that one can measure the impact of all sorts of resources in online reference managers, unlike in the limited bibliographic indexes.

I think it could be reference managers don't always reflect readership: one could save a reference and forget about it all together later (so many articles, so little time...). On the other hand, citation counts might suffer from the same problem, as many scientists use a "rolling citation" from other articles citing an earlier article, without actually having read the article themselves.

Priem et al. also presented lately a study about web citations and WoS citations, based on data from the seven PLoS journals, but I think I'll wait for the journal article to cover it in the blog.

Li, X., Thelwall, M., & Giustini, D. (2011). Validating online reference managers for scholarly impact measurement Scientometrics DOI: 10.1007/s11192-011-0580-x

Reinventing Discovery, Part II

2011-12-14T18:08:00.000-08:00

This is the second part of my review of Michael Nielsen's book "Reinventing Discovery - The New Era of Networked Science" (first part is here). Last time we talked about Galaxy Zoo, the Polymath Project, and why scientists don't (usually) do Wikis. This time I'd like to focus on the book parts which talk about ArXiv

ArXiv

First of all, I have to say I've been using ArXiv extensively lately as part of the ACUMEN project, trying to figure out who and what can be found there. The place is a bit of a mess - it's not Pubmed - but it still left me in awe, because not only that most of the astronomers I've searched had papers there, most of them contributed at least one of the papers themselves (you can see who submitted the paper).

ArXiv comes with a service called SPIRES (now inSPIRE) which can tell you how many times a paper was cited, who's citing who, and so forth. This way, it's possible to measure at least some of the impact of preprints (if you're a high-energy physicist). So, not only ArXiv makes the scientific communication faster, it also helps evaluate the impact of this kind of communication more accurately.

Unfortunately, not everybody gives ArXiv the honor it deserves. Nielsen tells how when he was writing the book, a physicist told him that Paul Ginsparg, ArXiv's creator, was wasting his talent on "collecting garbage", reflecting a disregard certain scientists have for "mere" tool builders. I don't know if this attitude is common in the scientific community, but it's discouraging nonetheless.

Open Access can be problematic

Citizen science isn't always all that - in the Polymath Project, there were people with good intentions but not much knowledge, their contributions didn't have much value to the project and had to essentially filtered out.

Misinformation - premature publications , especially in fields the mainstream media takes interest in, can spread far and wide, confuse the general public and discredit research projects in the eyes of the public.

How we can be more open (if you're reading this, you probably don't need these suggestions).

In the last few pages of the book, Nielsen suggests practical steps toward open science. A scientist can upload old data, code, etc. online for reuse (be sure to tell people how to cite it!); He/she can open a blog, contribute to other people's open science projects, or try to create a new one. Nielsen advises to "be generous in giving other scientists credit when they share their scientific knowledge in new ways" which I think is an excellent advice, even though the formatting and style guides are a bit behind the times when it comes to social media.

All in all, Reinventing discovery is a great book, however, I was a little disappointed to find only a small section dedicated to science blogs. The author explains that he had enough of the hype around blogging and that he doesn't want "to cover that well-trodden ground again", but I think the book could have benefited from a few more pages about the subject (yes, I know I'm not very objective here...). Also, though the book deals with - and recommends - open access, it isn't under Creative Commons licence (you can read why here).

Nielsen, Michael (2011). Reinventing Discovery Princeton University Press Other: 9780691148908

Reinventing Discovery: Book Review, Part I

2011-12-07T14:24:00.000-08:00

In Arthur C. Clarke's story "Into the Comet" he describes a spaceship with a computer malfunction that dooms all abroad to eventual death by starvation/oxygen deprivation, whichever comes first. The solution is a device older than the computer: the abacus. The entire crew ran calculations on acabi, and they make their way out of the comet's nucleus successfully. That is an extreme example of citizen science (or oh-my-God-we're-all-going-to-die science) but it shows the principle, that collaboration by a large number of people can solve very complicated problems. Michael Nielsen's excellent book, 'Reinventing Discovery' tells us about many such examples, though in most of them participants have to do a lot more than just calculate without thinking.

Source

Take 'Galaxy Zoo': volunteers can help classify galaxies (it turns out people do it faster and more accurately than a computer). It all began when one overworked grad student, Kevin Schawinski, wanted to prove that elliptical galaxies aren't always old, but had simply too many galaxies to go through in order to prove his theory. He and a post-doc, Chris Lintott, joined forces and opened a website which allowed anyone to come and classify galaxy photos. The project is an enormous success, with 22 scientific papers so far and the spin-offs Galaxy Zoo 2 and Galaxy Zoo:Hubble.

Another story Nielsen recounts is the story of the Polymath Project: Fields Medal recipient Tim Gowers posted a mathematical problem in his blog and asked for a collaborative efforts. Twenty-seven people wrote 800 comments and solved the problem within 37 days. Now there is a Polymath blog which keeps up the good work.

These projects were a success, but Nielsen also studies failed projects and the reasons for their failure. He argues (which I wholly agree!) that scientists are rewarded by writing as many good scientific papers as possible. Contributing to, say, Wikipedia, essentially takes away time from research and gives nothing in terms of academic reputation.

Galaxy Zoo is a success because it gives astronomers something to write about, and it's possible the Polymath project succeeds because it A. involves people with tenure and B. involves people who want to be noticed by people with tenure.

Personally, I think the solution to scientists' reluctance to cooperate in collaborative projects is simple: put them in a spaceship and tell them they won't be able to make it home until they collaborate. However, it is possible the oxygen run out while they'd argue about whose name gets to be first in the authors' list. Also, spaceships are very costly.

Next part: what Nielsen has to say about Arxiv and the future of open science.

Bora's Review

Joerg Heber's Review

Michael Nielsen talks Open Science in a TED event:

Nielsen, Michael (2011). Reinventing Discovery Princeton University Press Other: 9780691148908

Generic drug trials: more transparency needed

2011-08-18T19:04:00.001-07:00

The New York Times reported a couple of days ago that "Federal regulators and the generic drug industry are putting the final touches on an agreement that would help speed the approval of generic drugs in this country and increase inspections at foreign plants that export generic drugs and drug ingredients to the United States." The generic drug manufactures will pay an annual fee of 299$ million dollars, so that the FDA will be able to hire more reviewers and speed up approval of applications for marketing of generic drugs. The question is: what do we know about the generic drugs marketed today?

Van der Meesch et al. (2011) published in PLoS One a methodological systematic review about Bioequivalence trials which compared generic to brand-name drugs published between 2005 and 2008. They searched Medline for appropriate papers, as well as journals which regularly publish bioequivalence trials. Out of 134 papers that reported bioequivalence trials between brand-name drug and generic drug, 55 didn't include the reference drug name and were excluded. The final sample consisted of 79 papers which dealt with assessment of the bioequivalence of generic and brand-name drugs.

What do the FDA and the EuropeanMedicine Agency (EMA) demand from a generic drug?

The FDA wants to know three things:

Cmax - maximum plasma drug concentration

Tmax - time required to achieve a maximal concentration

AUC - total area under the plasma drug concentration-time curve

The 90% confidence intervals for the ratios (test:reference) have to be between 80% and 125%. The EMA wants to know only the Cmax and the AUC.

Source: Generics – equal or not? (Birkett, 2003)

Experiments of bioequivalence are usually randomized crossover trials. They are conducted on healthy volunteers by administrating one dose of the drug. Seventy-three (92%) of the trials were indeed single-dose trials (6 (8%) were multiple-dose) and 89% of the single-dose trials reported bioequivalence. About a third didn't report CIs for all the FDA criteria, and 20% didn't report the required EMA criteria. Only 41% of the papers reported funding, 25% had private funding.

As always, the study has limitations: it included only papers from the years 2005-2008 and relied on FDA guidelines from 2003 and EMA guidelines from 2001 (updated 2008). It's also possible that they researchers' search in Pubmed didn't retrieved all the relevant papers.

In conclusion, there is a serious lack of available data about generic drugs. The authors point out that while 1,661 generic drugs were approved by the FDA during the study period, there weren't any data available about trials assessing generic drugs on the FDA and/or EMA sites. The authors also hypothesize that such a small percent (10%) of failed bioequivalence trials seem unlikely and suggested a possibility of publication bias.

van der Meersch, A., Dechartres, A., & Ravaud, P. (2011). Quality of Reporting of Bioequivalence Trials Comparing
Generic to Brand Name Drugs: A Methodological
Systematic Review PLoS One : 10.1371/journal.pone.0023611

The Wikipedia Gender Gap, Part III

2011-08-10T00:12:00.001-07:00

In part I and part II, we discussed several of the gender gaps in Wikipedia. In this part, we'll talk about reverted edits, blocking, and their association with female and male editors. .

Blocking

The hypothesis here was that "Female editors are less likely to be blocked." However, there wasn't a statistically significant difference in the percentage of females blocked (4.39%) and males blocked (4.52%). Surprisingly, females were significantly more likely to be blocked indefinitely (3.85% and 3.32% respectively). Females were also significantly more likely to be reverted for vandalizing Wikipedia’s articles (3.26% and 2.11% respectively). This should be taken with a grain of salt, because the proportion of users who self-reported their gender and were blocked or reverted for vandalism was even smaller than the baseline.

Reverted Edits

Are female editors more likely to have their early edits reverted? To find out, the editors first "cleaned" the data from the reverted edits that were vandalism damage repair and took into account only reverts that were made within one week of an edit (more than 95% of the edits in the data set). For the seven first edits, the average reverting percent for women was significantly higher than that of men. Beyond those first edits, men and women's chances of having their edits reverted are similar.

Are women more likely to leave Wikipedia after their early edits were reverted? The authors answered this question by building a Cox regression model, to find out which factors are associated with changes in activity life span. The model included gender, the number of edits made in the first 24 hours of editing Wikipedia, the proportion of edits made in the first 24 hours

that were reverted for vandalism-related reasons, the proportion of edits made in the first 24

hours that were reverted, but not for vandalism-related reasons, and %RvNV×Gen, an interaction term between %RvNonVandal (the non-vandalism reverted edits) and gender, which was used to study the interaction between gender and reverts for non-vandalism reasons.

All the variables except for %RvNV×Gen were significantly associated with activity lifespan. The more edits an editor made during her/his first 24 hours, the longer her/his lifespan was likely to be. Shorter life span was associated with having early edits reverted. Even after taking said factors into account, being female still had a strong association with shorter lifespan.

While early reverts tend to make a lifespan shorter for both men and women, the likelihood of their departure wasn't gender-related. Female editor was just as likely to leave after being reverted as a male editor. In short, it's not that women "give up" more often than men when being reverted, it's that they were more likely to be reverted.

In Conclusion

Why doesn't Wikipedia have more women editors? This isn't the first time this question has been widely discussed. Last year, after a survey that found that only 13% of the Wikipedia's editors were women, the NYT published an article about the subject, which lead to some serious discussions and blog posts. Sue Gardner, Executive Editor of the Wikimedia Foundation, wrote a blog post including several of the reasons women supplied when asked why they hadn't edit Wikipedia. Answers varied and included reasons like the less-than-friendly interface, lack of time, lack of self-confidence, and an overall atmosphere of misogyny.

Now, since we know women *do* edit Wikis and *do* deal with less than friendly interfaces (have you ever, for example, tried to convince a Live Journal post to behave?) one must wonder if the main problem is, indeed, a culture that isn't women-friendly enough for most women to make the effort to fit in.

Lam, S., Uduwage, A., Dong, Z., Sen, S., Musicant, D. R., Terveen, L., & Terveen, J. (2011). WP:Clubhouse? An Exploration of Wikipedia’s Gender

Imbalance WikiSym’11, October 3–5, Mountain View, California

The Wikipedia Gender Gap, Part II

2011-08-09T23:04:00.000-07:00

In part I we talked about the small percentage of female editors in Wikipedia and their shorter editing life span. In this part we'll talk about content areas female and male editor focus on, coverage of female and male-related topics and involvement in editing controversial entries.

Content areas

The authors divided the data from the January 2008 data dump into 8 main areas: Arts, Geography, Health, History, Science, People, Philosophy and Religion. Then, they checked the focus areas of each editor's activity. The authors found that men focused more on Geography and Science, while women focused more on People and Arts.

January 2008 Gender distribution of editors in eight interest areas. Editors can be categorized into more than one area

The reason these data look different than those presented earlier is that they are taken from a different data pool (2008 as opposed to the more recent data used earlier).

Topics Coverage

Are female-related topics covered in Wikipedia as well as male-related topics? The authors used their gender data to determine whether an article is of more interest to women or to men. Since there are so few female editors, the metrics were "subject to high relative variance and noise" so they had to use only high-activity articles where gender was known for at least 30 editors. Articles shorter than 100 bytes were exclude because they usually redirected to other articles. The authors ended up with a sample of 59,579 articles.

Articles were declared "male" if they were in the bottom quintile (lowest 20%) of female editing activity, "neutral" if they were in the third (center) quintile, and "female" if they were in the top quintile.

Male articles are significantly longer than female articles (33,301 and 28,434 bytes respectively, t-Test, p < 0.001). Neutral articles are the longest at 36,511 bytes. Since the authors used the articles' length as a crude measurement of quality, they concluded that coverage of female topics is indeed lacking. They hypothesized that neutral articles are longer because they appeal to editors of both genders and therefore receive more overall attention.

For an additional analysis, the authors used the movie recommender web site MovieLens, which has self-reported gender information from over 80% of users who started using MovieLens before May 2003 (when they stopped asking about gender). 32% of the site's users were females. The authors mapped each movie to its Wikipedia article and excluded movies with less than 10 known-gender raters or movies which had no article. The remaining data set included 5,850 movies. The Article Length was the dependent variable, "Movie Gender" the independent variable and Movie Popularity, Movie Quality and Movie Age were the control variables. Articles about "male" movies were longer than those about "female" movies.

However, when articles about Nobel Prize winners and recipients of the Academy Award for Best Actor/Actress were analysed, it was found that they are about of equal length. So, the length gender gap isn't noticeable for very popular and/or important articles.

Controversial Topics

The authors hypothesized that "Females tend to avoid controversial or contentious articles." They determined controversial articles according to whether the articles were protected or not, reasoning that Wikipedia tend to lock articles which are often vandalized or subject to content disputes. 5.20% of the “female” articles were protected, compared with 2.39% of the “male” articles. Female editors are actually more likely to be involved in controversial articles.

Next time: are women less likely to be blocked? Are edits by women more likely to be reverted?

Lam, S., Uduwage, A., Dong, Z., Sen, S., Musicant, D. R., Terveen, L., & Terveen, J. (2011). WP:Clubhouse? An Exploration of Wikipedia’s Gender
Imbalance WikiSym’11, October 3–5, Mountain View, California

The Wikipedia Gender Gap, Part I

2011-08-07T19:18:00.000-07:00

Wikipedia editing is a men's club. We already talked here about the lack of Wikipedia female editors (barely 13% of the editors are women). However, that survey was self-selecting and most of the participants (75%) used Wikipedia in non-English languages. Now, Lam et al. (2011) present their analysis of the gender imbalance in English Wikipedia. They took most of their data out of the January 2011 data dump, as well as from the Wikipedia API and the January 2008 and 2010 data dumps.

In Wikipedia, editors can specify their gender in their accounts' settings, place a gender user box in their User page, or mention their gender in their User page description and discussion. The authors collected data from the accounts' settings and from the gender user boxes through the Wikipedia's API. They didn't check whether the editors refer to their gender somewhere else as that would have been too progressed for the techniques they used. The final sample included 113,848 users. Only 2.8% of the Wikipedia editors report their gender, but the authors found that dedicated editors tend to state their gender more often: while only 6.5% of the editors who had at least ten edits stated their gender, 14.1% of those who had over a hundred edits and 34.7% of those with at least 1,000 edits did so.

The overall gender gap is still in place

Out of the 38,497 editors who started edited in 2009 and specified their gender, only 16.1% were women. To add to this, 16.1% of those accounts may have belonged to women, but they only did 9.0% of the edits. Male editors make almost double the edits female editors do. Women are only 6% of the editors with over 500 edits.

Life and death of editors

An editors begins her or his life in the first edit date and "dies" after more than six months of inactivity. Women "die" sooner, while men tend to live on.

The gender gap is consistent

The gender identification methods described earlier were introduced to Wikipedia in different times (gender user boxes in December 2005 and gender preference settings in January 2009). Since men usually "live" longer in Wikipedia, the authors could only compare the users who have joined Wikipedia after a gender identification method was introduced (otherwise they would have just carried the survival rate bias on and on in the analysis). The gap has remained more-or-less the same since December 2005.

That's it for this part. Next time: Is there a difference in content areas between women and men? Do women editors tend to avoid confrontations?

Talk about your favorite celestial body

2011-07-31T18:15:00.000-07:00

Webometrics researchers adore physicists, astronomers, and so forth, not only because they boldly research places where no one has gone before*, but because they have a very good Web presence, from blogs to Wikis to depositing in ArXiv. That is unlike scholars from other disciplines, without naming names** which still haven't made it out of the Hotmail age.

Ohtake et al. (2011) developed a system through which planetary scientists can share observation data about a planetary body while discussing it online. They mashed up two services: Google Earth and Twitter (both have APIs), as well as prepared a MySQL database that "connects the mash up components and provides backend functions of the system."

The users can put pins on any point, view the thread which is connected to any pin's location and write their own comments. The system makes it easier to have discussions about a certain location while viewing it, as well as saving the threads regarding said location.

Ohtake, S, Demura, H, Hirata, N, & Terazono, J (2011). Development of a GIS-Based Online Discussion System for Scientists with Google Earth API and Twitter 42nd Lunar and Planetary Science Conference

*And unlikely to go anytime soon, dammit. Not that I'm bitter.

**Philosophers

More about t-citings

2011-06-27T14:32:00.000-07:00

Several months ago I blogged about Priem & Costello's t-citings paper "How and why scholars cite on Twitter". Now Weller, Dröge & Puschmann have done further research about the subject, by analyzing tweets from two major scientific conferences.

They collected tweets from the World Wide Web conference 2010 (WWW2010, #www2010) and the Modern Language Association Conference 2009 (MLA09, #mla09), starting two weeks before each conference and ending two weeks after.

WWW2010 Vs. MLA09

The authors considered tweets with links to websites as external citations. URLs were classified into the following categories:

Blog: Blog posts/commentaries in personal websites
Conference: Official conference websited
Error: Bad URL
Media: Photos, videos, graphics, etc.
Press: non-scientific publications from newspapers, journals, etc.
Project: Official websites of research groups, scientific projects or project results
Publication: Scholarly publications
Slides: Presentation slides
Twitter: In-Twitter links or Twitter-related sites
Other: Everything that didn't fit into the categories above.

Almost 40% (39.85%) of the WWW2010 tweets included URLs, and more than a quarter (27.22%) of the MLA09 tweets had URLs.

Tweets classified into categories:

Participants of MLA09 preferred linking to blogs and press articles, while the WWW2010 participants preferred various media items and blogs. The WWW2010 number of links to presentations and publications was much higher than the number of those in MLA09, which had zero slides linked and only 3 unique publication URLs.

Retweets: Bora Z wins the WWW!

Counting retweets can be problematic, since they don't always start with RT @user. The authors had to manually classify tweets to locate the retweets. In both conferences the top retwitteres weren't retweeted often themselves.

Top retweets usually include URLs:

While this work is interesting, it's definitely preliminary. The authors promise to analyze citation patterns over time, study differences between disciplines and more in the future. I hope we'll see more research about those subjects soon.

Weller, K., Dröge, E., & Puschmann, C. (2011). citation analysis on twitter MSM2011 - 1st Workshop on making sense of Microposts, 1-12

Coverage of common causes of death in the UK media

2011-06-09T17:10:00.000-07:00

Is there a correlation between the diseases you read about in the news and what is actually likely to kill you?

Williamson, Skinner and Hocken (2011) studied the 10 most daily read newspapers in the UK s (The Sun, Daily Mail, The Mirror, The Telegraph, The Times, Daily Express, Daily Star, The Guardian, The Independent and the Financial Times) for a year, in order to see whether there's a correlation between the media reporting of illness and death and actual statistics.

Most common causes of death in the UK, according to the Office for National Statistics (table from the paper)

They searched each paper's site and recognized 18,482 articles covering the most common causes of death in the UK. They used 'media friendly' terms when it was necessary (for example: 'heart attack' instead of ‘ischaemic heart disease’).

The most common conditions reported were the Flu/pneumonia (6525 articles, 35.2%), ischaemic heart disease (3849 articles, 20.8%) and dementia (2577 articles, 13.9%). The least reported conditions were obstructive pulmonary disease (COPD) (95 articles, 0.5% of total) and heart failure (547 articles, 3%).

Pneumonia: third most common cause of death in the UK

In comparison with the number of deaths they cause every year, the Flu ⁄ pneumonia, prostate cancer, dementia and breast cancer have been mentioned extensively in the media. On the other hand, Cerebrovascular accidents (CVAs) and chronic obstructive pulmonary disease (COPD) are very underrepresented in the media.

The study suffers from several flaws: for one, the researchers don't know in which context their search terms appeared in the media; why were these diseases reported? They hypothesize, for example, that "prostate cancer" could have been reported because of the coverage of the Libyan Lockerbie bomber, Al-Meghari, or that the search term 'flu' could actually been 'swine flu' but they can't be sure.

There is, in my opinion, a large difference between a story mentioning prostate cancer as the reason for Al-Meghari's release from prison and a story about prostate cancer from the medical point of view. The Swine Flu has been indeed covered intensively lately, but that doesn't mean that the 'regular' flu has been covered, even though it's a common cause of death. The Swine Flu falls under 'health scare' while the regular flu doesn't, and treating both as 'flu' kind of misses the point. This study is more about "how many times diseases' names appear in the press" than about "the media and representations of common diseases".

Swine Flu: sexier than the regular flu

Williamson, J.M., Skinner, C. I., & Hocken, D.B. (2011). Death and illness as depicted in the media International journal of clinical practice, 65 (5) : 21489079

In Scientific American's Guest Blog

2011-05-31T07:18:00.001-07:00

I'm glad to say that you can now read my post about health reporting and its sources over at Scientific American's Guest Blog.

You're just a number: introduction to the h-index

2011-05-20T17:19:00.000-07:00

Measuring a single scientist's output has always been problematic. Why? First, in order for the statistics to be reliable, the scientist has to produce a considerable publication output and get cited. That takes time. Second, measures like research productivity, number of publications and citations don't always correlates. Measuring the output of journals and universities has been far more reliable than measuring that of one person.

Suggested by physicist Jorge Hirsch, h-index (2005) offers an attractive way of quantifying one's scientific output as a single number. The index is defined as:

“A scientist has index h if h of his or her N_p papers have at least h citations each and the other (N_p − h) papers have ≤ h citations each” ().

So, if a scientist published at least ten papers, which each were cited at least ten times, her h-index is ten. A zero h-index, on the other hand, says that the scientist perhaps published papers, but is yet to have an actual impact.

The h-index is attractive because it takes into account both the number of publications and the number of citations. It isn't phased by "one hit wonders", but favors a body of work that each of its components has at least a certain impact (citations).

Problems and disadvantages

Which database to use? Different databases cover different journals, conferences, etc. Web of Science, for example, has better coverage of STEM than of the humanities, which tend to publish books rather than papers. Using Google Scholar will likely inflate the h-index.

Which field are you in? Larger fields mean a larger potential for citations, resulting in a higher h-index.

You aren't a number! (Or at least, not just *one* number). Reducing scientists to a single number ignores other factors, such as their teaching skills and ability to collaborate. Can an entire career really be described as a single number?

Source: PhD Comics

The age factor: The older the scientist gets, the longer she had to publish and get cited. Younger scientists are at disadvantage with the h-index.

Relevance: Since the h-index doesn't decrease, it can't tell whether a scientist is still active and/or where her work is still relevant for others in her field.

Since the h-index is a single number, scientists with the same h-index can have very different numbers of papers and citations. In the following table, scientist A and scientists B have the same h-index, but scientist A has far more citations in the overall raw calculation.

Source: Bornmann & Daniel, 2008

Because of the h-index many problems, offering new corrections to it, or coming up with other indices altogether is the official new sport for bibliometricians. The new indices are supposed to offer a better way to make decisions about promotions and grants, but despite all the efforts, it seems that the way to the promised tenure will continue to be paved with peer evaluation.

Bornmann, L., & Daniel, H. (2007). What do we know about the h-index? Journal of the American Society for Information Science and Technology, 58 (9), 1381-1385 DOI:10.1002/asi.20609

Bornmann, L., & Daniel, H. (2008). The state of h index research. Is the h index the ideal way to measure research performance? EMBO reports, 10 (1), 2-6 DOI: 10.1038/embor.2008.233

Hirsch, J. (2005). An index to quantify an individual's scientific research output Proceedings of the National Academy of Sciences, 102 (46), 16569-16572 DOI: 10.1073/pnas.0507655102

Students and pseudo-scientific beliefs

2011-05-07T13:52:00.000-07:00

"The Dean insists that we add creationism and crystal theory and spiritualism to the curriculum."

"They already have those--"

"Not as equal time in the physics and chemistry departments"

Fallen Angels (Niven, Pournell and Flynn, 1992)

Luckily, chemistry and physics departments aren't forced (yet) to add these kind of courses to their curriculum, but that doesn't stop the students from believing in all sorts of pseudoscience, from astrology to faith healing. Since 1988, students (mostly freshmen and sophomores) at the University of Arizona were given a questionnaire in order to determine their attitudes toward science and pseudoscience, as well as examine their basic scientific knowledge. Normally, the students take the survey during the first week in General Education astronomy courses, before any discussions in class about astrology and/or pseudoscience.

Do students consider astrology a science?

Less than a third of the students "disagree" or "strongly disagree" with the statement "The position of the planets have an influence on the events of every day life." Female students tend significantly more to believe that astrology is "sort of" or "very" scientific.

Students majoring in science did better than students studying non-scientific majors:

Strangely, the findings of the National Science Foundation (NSF) in the U.S. regarding astrology are considerably better: in 2006, 65% of the Americans said that astrology was "Not at all scientific", in comparison with 5% who thought it was "Very scientific", 26% who thought it was "Sort of scientific" and 4% who didn't know. Female respondents tend to think more than male respondents that astrology is "Sort of scientific" (29% and 23% respectively). Five percents of both genders believe that astrology is "Very scientific".

The authors aren't sure why the NSF results and their differ so much. They mention that the NSF survey takes place over the phone, as opposed to their paper-based survey. Also, the survey is given as a part of an astronomy course and the similarities between "astrology" and "astronomy" might have confused the students. While the NSF survey population comes from all over the U.S., this survey's population is mostly for the Southwest, so the sample might be location-biased.

Science literacy and astrology

There is a negative correlation between belief in astrology and science classes. The more science classes student take, the less they tend to believe in astrology.

On the other hand, there was only a small (though significant) difference in the number of correct answers to the scientific knowledge questions between those who thought astrology wasn't scientific and those who did. Out of 15 questions, the former answered, on average, 12.5 questions correctly (83%), while the latter answered 11.6 correctly (77%).

Pseudoscience and scientific knowledge

Nearly 39% of the students think that "Some people possess psychic powers". About 32% have no opinion about the matter, and only about 29% "Disagree" or "Strongly disagree". Things are a bit better with "Some ancient civilizations were visited by extraterrestrials": only 15% or so said they "Agree" or "Strongly agree". More than half of the students (51.66%) didn't have an opinion about the subject. Less than 40% "Strongly disagree" or "Disagree" that "Faith healing is a valid alternative to conventional medicine".

In conclusion, it seems that scientific knowledge doesn't necessarily make people (at least Arizona students) disregard pseudoscience beliefs. However, studying science correlates positively with rejection of pseudoscience such as astrology.

Sugarman et. al (2011). Astrology Beliefs among Undergraduate Students Astronomy Education Review

Pig's blood, tobacco control and mass media

2011-04-04T07:07:00.000-07:00

Pigs play an important role in the western culture, mostly as guests of honor in many meals. A less known role of pigs, or, to be precise, of pigs' blood (‘porcine haemoglobin’) is as part of what is called ‘biofilter’ in certain cigarette brands. Developed by Greek researchers, said 'biofilter' is supposed to make cigarette smoking healthier (it doesn't).

According to Valavanidis, Vlachogianni & Fiotakis (2009)

"Filters (so called “bio-filters”) with antioxidant compounds impregnated in active carbon canaffect only marginally the composition and toxicity of solid and gaseous phases of cigarette smoke."

Marketed as healthier, the BF helped the cigarette company SEKAP to become the second largest Greek cigarette manufacturer, with the BF cigarettes capturing 6% of the Greek market the month after they were launched. The company also export their cigarettes to Europe, Asia, Africa and the Middle East. By the time healthier smoking claims were outlawed by the Greek government, in 2002, the product already acquired a 'healthy' image.

An Australian organization decided, as part of a tobacco control project (funded by the cancer institute of New South Wales) to alert the media, through press releases, to several tobacco-related issues. They issued a press release in March 2010 ("New book on pig products reveals problems for Islamic, Jewish and vegetarian smokers"). It is important to note that at least in Australia, tobacco companies aren't obligated to reveal their cigarettes' ingredients.

As part of the research, the authors studied the coverage of the press release online. The story was covered all over the globe, including by the Daily Mail, the Calcutta News and even by The Colbert Report. The less thrilling part was that no media, except for an Israeli TV channel and a group of journalists one of the authors encountered during a visit to Indonesia, contacted the authors. They all based their coverage on a newswire (AAP) media release.

The pig blood's news created confusing, and author Simon Chapman received emails, mainly from Muslims, who wanted to know which cigarette brands were 'safe'. The the South African National Halaal Association issued an anti-smoking leaflet (fig. 1). The Iranians blamed 'the Zionists' for the 'tainted cigarettes'. Cigarette companies such as Japan Tobacco International, Philip Morris were quick to publish denials.

Overall, the authors consider 'unorthodox' framing was considered a success in alerting the public to the secretive nature of the tobacco companies and the lack of regulation on tobacco products. I think that for Orthodox Jews and Muslims it is another reason to stop smoking: I mean, dying of lung cancer and going to hell?!

Mackenzie R, & Chapman S (2011). Pig's blood in cigarette filters: how a single news release highlighted tobacco industry concealment of cigarette ingredients. Tobacco control, 20 (2), 169-72 PMID: 2117285

Valavanidis, A., Vlachogianni, T., & Fiotakis, K. (2009). Tobacco Smoke: Involvement of Reactive Oxygen Species and Stable Free Radicals in Mechanisms of Oxidative Damage, Carcinogenesis and Synergistic Effects with Other Respirable Particles International Journal of Environmental Research and Public Health, 6 (2), 445-462 DOI: 10.3390/ijerph6020445

International Women's Day and the science blogging gender gap.

2011-03-08T06:08:00.001-08:00

Warning: This post contains *gasp* feminist and non-politically correct opinions. Read at your own risk.

As anyone who reads this blog regularly knows, I've been working on characterizing Science Blogs which have over twenty posts at the Researchblogging.org aggregator, and posted there after January 1st, 2010. While my original sample had almost 200 blogs, I've decided to focus on private independent blogs and private blogs belonging to a blogging network (meaning of "private" here is "one or two writers and not a commercial blog). I ended up with 126 blogs*.

If you think you've seen these results before, it's because you probably have. Jennifer Rohn from "Mind the Gap" showed last year that women were considerably outnumbered in four major science blogging networks. This gap isn't limited to selective blogging networks, but exists in the Researchblogging.org aggregator as well, as Dave Munger showed. To quote Munger: "The gender ratio there closely mirrors the other networks." Wikipedia has the same problem: only 13% of the contributors are women.

I must say that the first time I saw the data, I thought "Wow, it looks like the percentage of women in Science Fiction at the 40s". Back then women were walking wombs (Heinlein), miserable, lonely scientists (Asimov) or silly housewives (Asimov again). The problem is that, well, Science Fiction moved forward since then, while the spreading of scientific memes to the public is still being done mostly by men.

So, where are all the women? I don't have a definite answer, but I can offer a few ideas:

Fandom - Fandom is a feminine sphere. Both genders watch television and read books, but in all my years in fandom, I've rarely seen men author fanfics, to the point that the default assumption is that a fanfic author is a "She".

A "Science" blog - What is a science blog? Or a research blog? RB is supposed to be open to all posts dealing with peer-review science, but I'm currently working on a list of peer-review journals cited in RB posts, and Literary, History or LIS journals are rarely cited. It is possible that once we take into account blogs dealing with peer-review research that aren't "officially" science blogs, the percentage of women will go up.

The second shift - Today, not to breast-feed until the kid can talk whole sentences is considered child abuse. And that's before we talked about picking up the kid from day care, helping older kids with homework and driving them to after-school activities. In many homes, somehow the mothers end up doing most of the work. However, the "Publish or Perish" rule is looming over everyone's head, mothers included.

The third shift - In "The Beauty Myth" Naomi Wolf pointed out that many women today feel the pressure not only to be excellent workers and excellent mothers, but to look great while doing everything as well. How is a woman to balance between being a scientist, mother and an aspiring model?

This post might seem kind of gloomy, but it's important to remember how much we progressed. Whenever I hear a female parliament member, a business woman, or a female professor claiming she's not a feminist, all I can do is wonder how would said woman lived her daily life without a bank account or a right to vote. Never take those for granted.

*Disclaimer: These are primary results and the final results might change a bit (if I decide to include other groups in the sample, for example. Please don't quote anywhere official without consulting me first).

Glott, R, & Ghosh, R (2010). Wikipedia Survey – Overview of Results UNU-Merit

State of the library and information science blogosphere

2011-03-05T07:39:00.000-08:00

Back around 2006, blogs were the height of fashion, like the Tamagotchi in 1996. Blogs, like Tamagotchi, need to be cared for regularly to survive. Torres-Salinas et al. (unfortunately behind a paywall) set out to check what happened to library and information science blogs in the years 2006-2009.

For the study, the authors selected to analyze the blogs indexed in the search engine Libworm (n=1108). Most of the blogs were from 2006 (n=1030), because Libworm stopped indexing new blogs since the beginning of 2007. The study's time frame was between November 2006 and June 2009.

Results:

Blogs are difficult to maintain. Even with the generous definition of an active blog as a blog which published at least one post a year, by 2009 only 622 blogs remained active, a drop of 43% from 2006. Out of the 1108 blogs active 2006-2009, only 572 blogs remained that way during the entire study (almost 52% became inactive).

When applying a more strict definition of "active" (at least one post per month between Nov. 06 and June 09) the numbers go down even more: from 804 blogs at the beginning to 454 at the end (fig. 1.). Blogs went extinct at a rate of 11 per month.

Fig. 1. Going down: LIS blogs publishing at least one post per month between November 2006 and June 2009 (Source: Torres-Salinas et al, 2011)

Top LIS blogs

The web-visiblity of each one of the 1108 blogs was calculated by PageRank, number of links from Google and Technorati authority. In table 4 of the paper, the authors show the top 30 blogs according to these indicators and in comparison to past papers (the ranking part is presented in fig. 2. here) .

fig. 2. Ranking of the 30 top blogs.

Most of the blogs were written in English, and the most frequently linked blogs were Blog of a Bookslut, John Battelle's Searchblog and Official Google Blog. The average number of posts per month for a blog in the top list was 63, and the highest PageRank was 8, for Official Google Blog and Stephen (no. 26 on the list).

Personal Vs. corporate blogs

Fifty-eight percent of the blogs in the sample were personal blogs, and they produced 79% of the posts, on average 301 per year. Corporate blogs have lesser visiblity, according to the rankings, and less impact.

Limitations:

Libworm's coverage of LIS blogs is limited, to say the least, and it mostly index British and American blogs (91.4%) of the sample. Also, the "active" blog definition of one post per year for yearly trend and one post a month for a monthly trend is very wide.

Conclusions

Note: Edited due to a comment. I'd like to thank the commenter.

While there was a decline in the number of active blogs in the sample, it is to be expected, due to the fixed sample in the study. The authors suggest that this marked decline of active LIS blogs in the study is because of the growth of Twitter, Facebook, etc. and bring a figure showing a decrease in research papers dealing with blogs and increase in papers about "Twitter or Facebook or Myspace or Web 2.0" to indicate that LIS scholars are more interested in social networks these days.

However, it is possible that while LIS scholars study and publish papers about social networks, they continue to use blogs as sources of information. Also, as far as I'm aware, blogs, Twitter, Facebook and Myspace are usually considered a part of Web 2.0, so I'm not sure why the authors chose to mention each one separately.

Fig. 3.

Number of articles and reviews about Web 2.0 and blogs indexed by ISI Web of Science published between 2006 and 2009

The authors also suggest that further research will validate their assumption, but that remains to be seen. Perhaps a sample of blogs from each year separately would have been better for that kind of a study.

Torres-Salinas et al. (2011). State of the library and information science blogosphere after social networks boom: A metric approach Library & Information Science Research :

doi:10.1016/j.lisr.2010.08.001

altmetrics11: Tracking scholarly impact on the social Web

2011-02-28T06:42:00.000-08:00

Altmetrics11 will take place in Koblenz, Germany, between 14 and 17 of June. My British prof, Mike Thelwall, will be keynote speaker!

You can submit a tw0-page abstract to the workshop until March 31. There're going to be lots of good people, like Jason Priem (of the T-citing glory), Paul Groth (of the chemistry blogs paper fame) and hopefully myself.

Misrepresentation of ADHD in scientific journals and in the mass media

2011-02-06T10:31:00.000-08:00

The scientific community often discusses the misrepresentation of health news by the media. A less discussed subject is misrepresentation of data in the scientific literature. Gonon, Bezard and Boraud used their knowledge about ADHD to find misrepresentations of data in scientific literature and mass media, and found that the misrepresentation problem often begins in the scientific literature.

1. Internal inconsistencies

The good news is that only 2 out of about 360 papers (Barbaresi et al and Volkow et al) had "obvious discrepancies" between results and their authors' stated conclusions.

The bad news is that both papers had been covered by the media, who mostly accepted their conclusions as gospel. Gonon et al say that in the 40 mass media articles they'd read about the Volkow et al. paper, "We have never read a mitigating statement saying that their results are open to the opposite interpretation although the authors explicitly raised this

possibility in their result section." Out of 21 the articles written about Barbaresi et al's paper, only The Guardian's article questioned the conclusions. More than that: out of the 30 times the Volkow et al paper was cited in scientific papers, in 20 the authors quoted its conclusion without pointing out the discrepancies.

2. Fact omission

It goes like this:

Summary: A totally controls B!

Result section: A controls B if C is present and D isn't.

In this part, the authors focused on papers dealing with "the association between alleles of the gene coding for the D4 dopamine receptor (DRD4) and ADHD." According to the authors, previous research has shown that while there is an association between higher frequency of a certain DRD4 allele and ADHD, it only occures in 23% of ADHD patients, as opposed to 17% of the control population. Out of 117 papers about ADHD research done in humans that mentioned the DRD4-ADHD connection, 74 mentioned the association in their summaries, but only 19 of those also mentioned the conferred small risk. All 25 papers which mentioned the association but didn't present data on it had the misrepresentation in their summaries. In review papers, out of 43 summaries, only 6 mentioned that the allele confer only a small risk.

The DRD4 gene, ADHD and the mass media - Media outlets have been known for their tendency toward genetic determinism (the "gay gene" for example) and so were quick to adopt the view that ADHD is "genetic". Out of 170 articles between 1996-2009, 168 mentioned that the DRD4 gene is significally associated with ADHD and out of those, 117 didn't mention the small risk and/or presented the raw data. 26 articles mentioned the 1.2 to 1.34 odd ratio but also stated there's a strong connection between the gene and ADHD. The authors' conclusion is that 82% of the articles misrepresented the association, a rate similar to that observed in the scientific literature.

3. Extrapolating basic and pre-clinical findings to new therapeutic prospects ("Hi, it worked on mice!")

The authors surveyed 101 papers dealing with the mouse brain for 3 common overstatements, and found that 56 overstated their conclusions. 23 even ~~fantasized~~ extrapolated about new therapeutic prospects. Naturally, those 23 papers were published in higher-impact journals and the overstatements made their way to the mass media. Out of 63 mass media articles, only 11 contained migtated comments.

Limitations

The authors consider their work to be qualitative rather than quantitative, since the selection of papers in the first case was not systematic. In the second and third cases the papers were selected after a systematic search, but the authors only highlighted one aspect of misrepresentation in each case. While the results correlate with misrepresentation in the mass media, there's no way to determine causation.

In conclusion

When I was young and working on a Biology degree, my (great) professor read us an abstract and said something along the lines of "They added that definitive conclusion in the end so the paper will be published in a better journal". While anecdotes aren't data, it does seem that scientists sometimes overstate their results in order to be published in higher rank journals.

It's easy to blame the mass media whenever people put on their tin hats, but the responsibility also falls on scientists to report their findings as accurately as possible, even outside the result section.

Gonon, F., Bezard, E., & Boraud, T. (2011). Misrepresentation of Neuroscience Data Might Give Rise to Misleading Conclusions in the Media: The Case of Attention Deficit Hyperactivity Disorder PLoS ONE, 6 (1) DOI: 10.1371/journal.pone.0014618

The language of science blogs

2011-01-22T11:01:00.000-08:00

Part of my dissertation is research of science blogs, and I finally have some results. I started with the relatively easy part of determining the language of science blogs and going to work my way to authors, journals, etc.

Sample:

All the blogs in http://researchblogging.org/ that have 20 posts and above listed in the site and the last time they posted there was in 2010-2011. That was in order to make sure the sample is of established science blogs and relatively current.

Results:

Overall number of blogs: 189

English: 162 blogs (85.714%)

Spanish: 8 blogs (4.233%)

Portuguese: 8 blogs (4.233%)

German: 6 blogs (3.174%)

Polish: 3 blogs (1.587%)

Mixed (German and English): 1 blog (0.529%)

Chinese: 1 blog (0.529%)

No surprises here, English is definitely the language of science blogs (said the Israeli PhD student...).

Graph:

Short hiatus

2010-12-13T06:40:00.001-08:00

I'm afraid I'm sick at the moment. Will write again as soon as I get better.

Yours

Hadas

Health reporters: between accuracy and deadlines

2010-12-06T13:08:00.000-08:00

"What's new, fresh, exciting, different, what people are going to say 'Gee, is that right'?

(Newspaper medical reporter, Leask et al., p. 4)

Being a health journalist isn't easy. There's the deadline, there's the expert who still hasn't called you back, the editor who wants a nice picture to go with the report...The authors of "Media coverage of health issues and how to work more effectively with journalists" interviewed sixteen Australian reporters, editors and producers in print, radio and TV in order to learn more about the challenges they face. They were asked about their job in general and about reporting avian/pandemic influenza in particular (the study took place between October 2006 and August 2007).

Newsworthiness

To be "newsworthy" a story has to have the right timing, at the pick of the hunt for news. Journalists are looking for sensation (the avian flu is the new Black Death!) for actual news (like a new medical development) and controversy. For TV, the story better have good visuals.

Journalists are aware of stories from other news outlets and choose which news to reports and from what angle so they'd be able to distinguish themselves from the competition. They often use local sources and aim for local audiences as ways of providing that interesting, novel angle.

Sources

Journalists' sources can be passive (PR) or active (calling experts and reading medical journals). Naturally, journalists prefer to interview people who are "accessible, independent, highly respected in their field, and preferably doctors." They want their sources to provide fast information, which can be easily digested by their audience. That is especially true for reporters without much scientific or medical background. In TV, the images often determine whether a story will be broadcast and how prominent it will be.

Ethics

The authors of the paper note that "as in other studies, journalists articulated an overwhelming commitment to keeping the public informed". Journalists try to reduce sensationalism by accurate, in-depth reporting. The journalists in the study often commented that they have to be critical and objective in their reporting. That's quite a different approach from the one which was common a few decades ago, when journalists were mostly functioned as science cheerleaders (read Dorothy Nelkin's excellent book "Selling Science" for more details).

Specialists

Like in the paper I blogged about in my previous post, the current paper found that "specialist health and medical reporters had much greater capacity to produce better quality health stories." These specialist reporters usually have better understanding of the technical aspects of medical issues. They also enjoy more autonomy within news organizations and rely more on their own contacts and sources than on PR. Their prestige as 'pros' allows them to advocate which stories are most 'worthy' to run.

Getting your health story in the news: a short guide for the confused scientist

Timing. Call the journalist in the morning, which is "peak story sourcing time". For broad distribution, try contacting the news agencies.
Be available. Return phone calls fast, drop other things if you have to.
Provide pre-prepared resources. Anything from definitions to images, and don't forget the sound-bite quotes.
Find a personal touch. Give the journalists an easy way to appeal to the average person.
Stay networked. Be in touch with medical reporters, provide them with scientific background and stories*
Appeal to ethical values. Find good moral reasons why the journalist needs to see (and write about) things your way.

Leask J, Hooker C, & King C (2010). Media coverage of health issues and how to work more effectively with journalists: a qualitative study. BMC public health, 10 PMID: 20822552

Nelkin, D. (1995). Selling science: How the press covers science and technology (rev. ed.). New York: Freeman.

*Feeding them might help as well.

Who writes health news?

2010-11-25T12:49:00.001-08:00

In times of financial difficulties, health reporters are usually the first to be let go. This is especially true if they actually know something about health (it makes them more expensive). Financial cutbacks mean that media outlets have to rely on news agencies or have non-specialist journalists report health. The authors of "Does it matter who writes medical news stories" are familiar with such problems (and their consequences), since they are reviewers of health news stories for the Australian Media Doctor site.

Media doctor sites are the media's health news watch dogs. They rate health stories according to criteria like "Quantified the benefits of intervention" and "Did not rely heavily on a media release". Today there are several media doctor sites in Canada, Hong-Kong, and United States (called Healthnewsreview, but works according to the same principles.

However, my favorite health stories watchdog is the British NHS "Behind the news" service: it takes a news story and discusses its sources, the type of study behind the story (cohort, double-blind, etc.), how it was conducted, the results and their interpretation, and the conclusion. All that in everyday language. It's brilliant.

Back to the study at hand: over the years (February 2004 to March 2009) 1,337 stories from 12 Australian media outlets have been reviewed. Out of those, 320 stories didn't have a byline; 193 were written by nonspecialist journalists; 415 came from news agencies (Australian Associated Press [AAP], Associated Press [AP], Agence France Presse [AFP], and Reuters) and 39 came from foreign media outlets (BBC, The New York Times, Washington Post, etc.); 142 stories were written by health/science journalists, and 228 stories were written by specialist health journalists (journalists who had 10 or more stories posted on the Media Doctor web site during the period of the study).

(Figure based on the paper's categories of authorship).

Quality speaking, stories by specialized health journalists scored the highest (59.6) while stories without bylines had the lowest score (44.1; you know it's bad when nobody wants to take credit for it). From the news agencies, AP scored highest on quality.

Is there a solution for low-quality health journalism?

The authors suggest, of course, that future journalists should be trained better regarding evidence-based medicine while they're still in college, and that major media outlets should invest in specialized health journalists. However, since the authors are aware these suggestions are costly, they suggest that some of the responsibility for good health reporting should lie with research institutions, funding bodies, and the researchers themselves, who all have to supply the media with accurate and balanced information about their studies. They see the promotion of good science as part of the requirements from those conducting health research, and believe better scientists-journalists collaboration will lead to better health reporting.

Wilson, A., Robertson, J., McElduff, P., Jones, A., & Henry, D. (2010). Does It Matter Who Writes Medical News Stories? PLoS Medicine, 7 (9) DOI: 10.1371/journal.pmed.1000323

The pursuit of happiness

2010-11-20T09:04:00.000-08:00

Happiness is an elusive term (though for most people, it includes one form or another of chocolate) and, to many people's surprise, it doesn't have much to do with money. Aaker, Rudd & Mogilner (forthcoming, 2011) reviewed the current happiness literature and came up with a list of five principles for happiness-maximizing ways to spend time.

Spend your time with the right people. People who socialize more often tend to be happier than those who spend most of their time alone. Happiness is associated with spending time with friends and family and not (surprise!) with your boss and co-workers. Two big happiness predictors are whether people have a "best friend" at work and whether they like their boss. Personally, ever since I recruited two friends to work with me, I feel sorry my scholarship doesn't allow me to spend more time at work...

Spend your time on the right activities. Ask yourself "will what I do right now become more valuable over time?" If you consider your time beyond the present moment, there is a bigger chance you'll engage in happy behaviors, like volunteering work and spending time with friends and family (assuming you enjoy their company).

Enjoy the experience without spending the time. You can feel pleasure just by thinking about a pleasurable experience. Sometimes people enjoy the anticipation more than the actual reward. So, it can be better just to plan the vacation, without actually taking days off work and going to God-knows-where. Daydreaming is good for us!

Expand your time. Well, the time doesn't actually expand - but the cliché of focusing on "the here and now" has some truth in it. Focusing helps people feel as if the time is moving slower. Engaging in a meaningful activity, like helping others, make people feel like their time is expanded. In general, people who have a sense of control over their time are happier. People feel they don't have time not only because they're busy, but because they aren't in control over said time.

Be aware that happiness changes over time. Getting older often means people enjoy peace and quiet, rather than new and exciting experience. Older people also tend to enjoy spending time with familiar people, rather than getting acquainted with strangers. Remember that what made you happy at twenty-five won't necessarily make you happy at fifty, and plan accordingly.

Aaker, J. L., Rudd, L., & Mogilner, C. (2011). If Money Doesn’t Make You Happy, Consider Time Journal of Consumer Psychology

Seek and ye shall find (friends online)

2010-11-14T09:47:00.000-08:00

Who makes new friends on social networks online? If we are going by the "rich get richer" assumption, we would expect to find that people who are already socially active will find even more friends on SNS. On the other hand, it's possible that those who have troubles forming offline relationships will socialize more on the Web (the "social compensation" model). The third possibility is the "seek and ye shall find" model: people who believe it's possible to create online friendships would be more likely to create them.

The sample in this study (Tufekci, 2010) was 617 students, 19 years old on average who use SNS. They were asked about the number of friends they kept in touch weekly offline (15 on average) and if they've met new friends online. In the qualitative section (175 respondents) they were asked whether they believed it was possible to meet new friends online or not, and why.

After analysis, Tufekci found that those who believed online friendships (N = 300) were possible were 52% more likely to have met new friends online than those who didn't (N=317). The only difference between the two groups was time spent online: those who were positive about online relationship spent about 23 more minutes a day online.

Surprisingly, African-Americans had about 67% higher odds of meeting new friends online, compared with whites. Gender and age didn't make any significant difference, and neither did the number of offline friends.

Why people don't believe in online friendships

Trust. Some respondents felt online identities aren't reliable.
Need for a face-to-face communication.
Difficulties in conveying emotions and creating intimacy online.

Why people do believe in online friendships

Some respondents felt online friendships are less judgmental, more open and less embarrassing.
Some respondents felt the important part in a relationship is the conversation, whether online or offline.
Experience. About 10% of the respondents who were positive about online relationships met friends/spouses online or have known someone who did.

Of course, the results of this study are relevant to the college population studied, so one can't generalize the findings to the rest of the population, but it is interesting that many of the "N-generation" still feel the need for a face-to-face interaction in order to form a friendship.

Tufekci, Z. (2010). Who Acquires Friends Through Social Media and Why?
"Rich Get Richer" versus "Seek and Ye Shall Find" Proceedings of the 4th International AAAI Conference on Weblogs and Social Media (ICWSM, 2010).

Introducing new vaccines into poor African nations

2010-11-04T17:17:00.000-07:00

The GAVI alliance (used to be called the Global Alliance for Vaccines and Immunizations) was founded in 2000 in order to help vaccinate children in poor nations. GAVI funds vaccines in any nation with a GNI per capita of less than $1,000. Glatman-Freedman et al. (published November 2010) investigated the factors involved in successful introduction of the Hib (Haemophilus influenza) and HepB (Hepatitis B) vaccines into poor nations.

The Hib and HepB vaccines are expensive. The basic battery of vaccines (Polio, Diphtheria, Pertussis, Tetanus, Measles and BCG) costs about $1 per child, but the Hib and HepB vaccines raise the cost to $7-13. Taking the new vaccines cost into account, it is very important to determine the best way to introduce them into poor nations.

The authors included in the study GAVI-eligible nations from the WHO African region (AFRO) with population bigger than half a million (35 countries overall).

The countries were included in one of three groups:

I. Countries where both Hib and HepB were introduced.

II. Countries where only HepB was introduced.

III. Countries where neither vaccine was introduced.

(Table and explanation from the original paper)

The authors looked at country-level governance indicators (political stability, government effectiveness, regulatory quality, rule of law, control of corruption and voice and accountability) and (as expected) found that mean scores for all indicators were highest at group I and lowest at group III.

Next, the authors tried to create a combined governance scoring, which consisted of the average of all the governance indicators of each country for each year. There was a significant difference.

Symbols represent means and error bars represent standard error of the mean. Grey plot background highlights the Pre-GAVI years, white plot background highlights the GAVI funding years. * p value smaller than 0.05, ** p value smaller than 0.01 (figure and explanation from the original paper).

Overall, the study indicated that the best way to predict poor African nations ability to introduce new vaccines is to determine their country-level governance. Good governance and political stability help nations attract both foreign aid and investments. Other than funding, the introduction of new vaccines requires trained personnel, cold chain capacity, the ability to reach remote locations, and safe disposal of needles and syringes. Hopefully, this study will be able to help GAVI to introduce new vaccines into poor nations more efficiently.

Glatman-Freedman, A., Cohen, M., Nichols, K., Porges, R., Saludes, I., Steffens, K., Rodwin, V., & Britt, D. (2010). Factors Affecting the Introduction of New Vaccines to Poor Nations: A Comparative Study of the Haemophilus influenzae Type B and Hepatitis B Vaccines PLoS ONE, 5 (11) DOI: 10.1371/journal.pone.0013802

How JAMA managed to avoid becoming an advertising platform for the pharmaceutical companies

2010-10-31T15:46:00.001-07:00

(Note: this is a follow up to my previous post).

In July 2005, JAMA began to require industry-supported studies to undergo independent statistical analysis. To see if this requirement affected the number of industry sponsored studies publicized in JAMA, Wager et al. (October 2010) looked for all randomized controlled trials (RCTs) published in JAMA from 1 July 2002 to 30 June 2008.

They classified the trials according to their funding sources: Industry funded (IF), joint industry plus nonindustry funding (J), industry supported (IS) (the pharma companies provide the materials but don't design or execute the studies), non-commercial (N) and funding not stated (NS). The broad 'industry' category included the IF, J and IS studies. The Lancet and NEJM were used as control (these journals don't have the same requirement).

Both the total number of RCTs and the proportion of industry RCTs decreased in JAMA after July 2005. In the mean time, the proportion of industry RCTs in NEJM and The Lancet rose significally. The number of industry-supported and jointly funded studies in JAMA went down about as much as the number of solely industry-funded studies.

In light of these fundings, the authors wonder (and rightly so) whether the pharma industry 'boycott' JAMA in response to its policy and what, exactly, it means about the RCTs published in The Lancet and NEJM?

Wager, E., Mhaskar, R., & Warburton, S. (2010). JAMA Published Fewer Industry-Funded Studies after Introducing a Requirement for Independent Statistical Analysis PLoS ONE, 5 (10) : 10.1371/journal.pone.0013591

How the NEJM became an advertising platform for the pharmaceutical industry

2010-10-30T17:33:00.000-07:00

These days it's common practice for authors, peer-reviewers and even editors of medical journals to declare conflicts of interest, if those exist. However, medical journals normally don't issue the same declarations. Journals publish regularly industry-supported papers reporting large clinical trials. Reprints of those trials are regularly bought by pharmaceutics companies and distributed to clinicians. The result is an increase of the journals' income as well as an increase in their prestige, since papers read by a large number of clinicians are likely to increase those papers' citation rates and the journals' impact factor.

In order to study conflicts of interest in journals, Lundh et al. (October 2010) chose six high-impact medical journals: Annals of Internal Medicine (Annals), Archives of Internal Medicine (Archives), BMJ, JAMA, The Lancet and NEJM and studied the proportions of industry-supported randomized clinical trials (RCTs). The authors focused on citations from 1996-1997 for 1995 papers and 2007 citations for 2005-2006 RCTs. They categorized funding as industry support, mixed support, nonindustry support and no statement about support.

Then came the tricky part: getting financial data from the journals about their income from advertisements, reprints and industry-supported supplements as percentage of the journals' total income as well as the total number of reprints sold. BMJ and Lancet (British) provided the data, but the other four journals (American) refused to do so. Given that lack of cooperation, the authors had to become creative. The journals' owners are the American College of Physicians (ACP) for Annals, the American Medical Association (AMA) for JAMA and Archives, and the Massachusetts Medical Society (MMS) for NEJM. The authors obtained their publicly available tax forms, that included data on the total income from all types of publishing. The societies, however, publish each more than one journal, so the authors couldn't determine incomes for individual journals. They had to calculate the relative income from industry sources, to which they received confirmation from ACP, but not from AMA and MMS.

In 2005-2006, 32% of the RCTs published in NEJM had industry support. However, for BMJ, only 7% of the RCTs were industry-supported. Declines in proportion of industry-supported trials were statistically significant for Annals and Archives.

Citations and industry support

For 1996-1997 trials, there was a significant correlation between citations and industry support for Lancet and NEJM. The correlation was statistically significant for all journals in 2005-2006. The authors write that "Industry-supported trials published in Annals, Archives and Lancet in 2005-2006 were cited more than twice as often as nonindustry trials and one and a half times more in BMJ, JAMA and NEJM".

Impact Factor

The authors calculated the IF of each one of the journals without the industry-supported trials. The NEJM had the largest decrease in IF, followed by the Lancet. The BMJ's IF barely changed.

Implications for mass media reporting

NEJM is the most prestigious medical journal in the world. Moriarty et al. (2010) found that it was the most cited source in news stories about cancer research (see my last post). If a third of the clinical trials published in NEJM are published by the industry, which means they are more likely to have positive results for the funding company (Lexchin et al., 2003), and taking into account that the NEJM is a very popular source of health news, that means the industry doesn't just gain influence with clinicians by publishing in NEJM, but with the general public as well.

See my follow-up post: How JAMA managed to avoid becoming an advertising platform for the pharmaceutical companies

Lexchin, J. (2003). Pharmaceutical industry sponsorship and research outcome and quality: systematic review BMJ, 326 (7400), 1167-1170 DOI: 10.1136/bmj.326.7400.1167

Moriarty CM, Jensen JD, & Stryker JE (2010). Frequently cited sources in cancer news coverage: a content analysis examining the relationship between cancer news content and source citation. Cancer causes & control : CCC, 21 (1), 41-9 PMID: 19784789

Lundh, A., Barbateskovic, M., Hróbjartsson, A., & Gøtzsche, P. (2010). Conflicts of Interest at Medical Journals: The Influence of Industry-Supported Randomised Trials on Journal Impact Factors and Revenue – Cohort Study PLoS Medicine, 7 (10) DOI: 10.1371/journal.pmed.1000354

Cancer coverage and its sources

2010-10-30T08:43:00.000-07:00

The average person acquires most of hers or his health knowledge from the media. The question is, where do the media acquire that knowledge?

Moriarty et al. (2010) tried to answer this question by studying the 2003 cancer coverage in 44 major American newspapers (they started with 50, but had difficulties obtaining full-text coverage for six of them). Their final sample included 3,656 in-depth cancer articles that were coded for topics, aspects of cancer continuum (prevention, treatment, etc.), sources and clinical trials.

The most frequently cited sources were research institutions (29.73%), followed by medical journals (12.30%), ACS (9.57%) and NCI (4.54%).

Ten most cited sources:

New England Journal of Medicine
Journal of the National Cancer Institute
Journal of the American Medical Association
Johns Hopkins University
Memorial Sloan Kettering Cancer Center
Genentech
Fred Hutchinson Cancer Center
Harvard University
H. Lee Moffitt Cancer Center
Science

Sources and story type

The most popular subjects were personal profiles of people with cancer, cancer research and cancer fundraisers/benefits. Research institutions were the most popular sources in almost every story type. In comparison, medical journals were mostly cited in cancer research stories. Pharmaceutical companies were rarely cited, and when they were, it was mostly in reports of cancer research and stocks.

Sources and the cancer continuum

Treatment was the most mentioned aspect of the cancer continuum (in nearly 75% of the articles). Detection was mentioned in about half of the articles. Of all aspects, prevention was the least likely to appear in stories.

Clinical trials and their tone

Out of the 317 stories about clinical trials, more than half (53.6%) cited a research institution. Medical journals were also cited frequently. The general tone of clinical trials coverage was optimistic (more than half the stories) with most of the other stories having a neutral or balanced tone. Articles that cited medical journals or pharmaceutical companies were significally more likely to be optimistic.

Overall, sources in cancer coverage change according to the type of the story. The ACS, for example, was frequently cited in awareness/education stories. Research articles frequently cited medical journals. The most interesting finding is that pharmaceutical companies aren't a main source for cancer stories (it could be, however, that those companies funded the research reported. The paper didn't look into funding sources). The authors mention that it's possible the reason for the large amounts of research institutions mentions is that the reporters rely on said institutions press releases.

Moriarty, C., Jensen, J., & Stryker, J. (2009). Frequently cited sources in cancer news coverage: a content analysis examining the relationship between cancer news content and source citation Cancer Causes & Control, 21 (1), 41-49 DOI: 10.1007/s10552-009-9432-x

Awesome

2010-10-30T04:00:00.001-07:00

Publishing Open Access is Good for Your Academic Reputation

2010-10-28T12:14:00.000-07:00

In the academic world, reputation is the currency of choice. "Reputation," of course, is a very loose term and can include anything from publishing in high-impact journals to being a good advisor to your students.

How does OA contribute to your academic reputation?

The first significant scholarly repository, arXiv.org, was started by high-energy physicists, but quickly expanded to include other scientific disciplines. Today, archiving in arXiv.org is practically a necessity for physicists. Archiving provides the physics community with faster communication, better access, and the opportunity for an unofficial peer-review, even before the work has been submitted to a journal. Unfortunately, journal publishing is still important for official purposes (promotion, tenure, etc.) and so libraries are still forced to buy physics journals.

Another example is PLoS. PLoS peer-reviewed journals charge the authors a fee in return for publishing, and papers are published under Creative Commons licences. PLoS journals probably wouldn't have been as successful (PLoS Biology had the highest IF in its category in 2009) if libraries were asked to pay for them. It pays off for authors to pay PLoS for the prestige of publishing in such high-impact journals.

Eysenbach (2006) found that immediate-OA papers in PNAS, in comparison with those who weren't immediately available in OA, were more likely to be cited earlier and more often. However, Davis et al., who studied papers from 11 journals published by the American Physiological Society, haven't found an increase in citations for OA papers in the first years after publication. They did find that these papers had significantly more downloads and unique visitors, which means OA papers reach wider audience.

Open Access also allows scientists to build reputation in places and among people who otherwise wouldn't have been able to read their researches (the MIT OCW is very popular in developing countries). Given how important citation metrics are to a scientist, publishing Open Access seems to be a very logical step, career-wise.

Willinsky, John (2010). Open access and academic reputation Annals of Library and Information Studies, 57, 296-302

Davis PM, Lewenstein BV, Simon DH, Booth JG, & Connolly MJ (2008). Open access publishing, article downloads, and citations: randomised controlled trial. BMJ (Clinical research ed.), 337 PMID: 18669565

Eysenbach, G. (2006). Citation Advantage of Open Access Articles PLoS Biology, 4 (5) DOI: 10.1371/journal.pbio.0040157

The medium is the joke

2010-10-25T20:26:00.000-07:00

In their paper "The medium is the joke: Online humor about and by networked computers" by Shifman and Blondheim (2010, pay-walled) the authors sampled 170 texts from "humor hubs" (that is, well-known humor sites), plus 80 videos from YouTube, ending up with 250 humorous items in their sample.

Manufactors, monopoly and the Microsoft menace In the absence of real alternative to Microsoft (though a friend once threatened me with installation of Linux) users make jokes which the authors interpret according to superiority theories (users are helpless to do anything but mock the ruler). Instead of throwing the Vista-installed laptop against the wall, the ~~victims~~ users show their frustration by making jokes. But it's not all Microsoft's fault: the authors suggest that because of the strong synonymity between Microsoft and the PC, people could be taking out their anger on Microsoft for "the failure of man and computer to interact harmoniously".

The users

Misusers: blondes, rednecks and usually other 'stupid' groups. Misusers are the people who can't work their computer properly.

Over-users: geeks; They are so familiar with computers they become emotionally attached to the ("You seriously consider devoting a web page to your computer. Not the brand, mind you, but the actual computer itself"). Over-users in jokes compromise their humanity and 'real' relationships in favor of their computers and cyberculture.

Abusers: The abusers "can be interpreted as the mirror image of the over-user". They use their computer to satisfy "the most earthly human drives" (pornography, frauds). Unlike computers, abusers have human-related faults.

Tech support

(source: the inevitable XKCD)

The tech support jokes address the gap between human expectations and how computers actually work. Tech supporters are considered a class of their own, "the closest parallel may, in fact, be the Oracle's Pythia or the priest in confession, mediating between man and the sublime divinity". The user has sinned and the computer stopped working. In order to communicate with the divine entity, the users turn to its priests, the tech support people.

I think the authors might have missed a sub-genre here, which I'll refer to as "tech-support are idiots" and is represented in the above XKCD comics. It's true there are many jokes about idiot customers, but tech-support personnel is also often mocked.

Anthropomorphism When computer become human. The sneezing computer, the icons attempting to kill one another on your desktop...These jokes are funny because of the sudden similarity between the very separated categories of 'human' and 'machine'.

Compumorphism The mocking of human groups by comparing traits associated with them to those of computers (computers are males because "they have a lot of data but are still useless"; computers are females because "no one but their creator understands their internal logic"). The traits allegedly shared by the computer and the group make them less than 'true humans'.

Neo-Luddism "If you can't join it, break it". A frustrated user is shown abusing a computer verbally and/or physically

Neo-luddites jokes can go both ways: either people laugh at the pathetic creature (the human, that is) or they relate to the rage.

I would like to thank Dr. Shifman who, at my request, sent me the paper. It has been both entertaining and informative. I wish the authors many citations.

Shifman, L., & Blondheim, M. (2010). The medium is the joke: Online humor about and by networked computers New media & society : 10.1177/1461444810365311

If sheep could tweet

2010-10-24T14:06:00.000-07:00

In Connie Willis' book, Bellwether, two researchers acquired a herd of sheep (they were studying fads). However, no sheep agreed to start a new fashion of pressing a button for food. What they needed was a bellwether, a fads-starting sheep.

Cha et al. searched for bellwethers ('influentials') on Twitter. They sampled more than six million active users ('active' means 'more than ten tweets'). They used three measures of influence: followers (indegrees), retweets and mentions. The number of followers indicated the size of the user's audience, retweets indicated the value of a tweet's content, and mentions indicated the user's ability to engage in conversation with other users.

The most followed users were news sources, politicians (Obama) and celebrities in general. However, the most retweeted users were the Mashable blog, Twittertips and TweetMeme, as well as businessmen (Guy Kawasaki) and news sites (they include The Onion under this category, which amused me greatly). Retweets are influential due to their ability to pass and reinforce a message to users way beyond the followers of the tweet's creator. The authors consider retweets citations of users' content.

Mentions - celebrities were often at the top of the 'most-mentioned' list. Since less than 30% of the 'mention' tweets contained URLs, the authors concluded that mentions are more about a person than about content.

The number of tweets and number of people a user follows (outdegrees) weren't significant influence indicators, simply because those were spammers.

Even ordinary users can rise to fame (mostly of the 15-minutes kind) if they have interesting content. Users like iranbaan, oxfordgirl and TM_Outbreak became immensely popular during the Iranian elections. Unlike those users, the Swine flu bellwethers, in the absence of catastrophic flu outbreaks, remained relatively stable in influence and popularity.

In conclusion

The number of followers doesn't necessarily make one a bellwether.
Retweets are mostly content-driven
Mentions are mostly user-driven
News sites do better at retweets, while celebrities get more mentions.
Influence on Twitter takes supplying plenty of content.

Cha, M., Haddadi, H., Benevenuto, F., & Gummadi, K. P. (2010). Measuring User Influence in Twitter: The Million Follower Fallacy ICWSM '10: Proceedings of international AAAI Conference on Weblogs and Social Media.

The Matthew Effect Strikes Again

2010-10-20T02:52:00.000-07:00

The new Bornmann, de Moya Anegón and Leydesdorff paper, published in PLOS ONE, shows that highly cited papers tend to reference other highly cited papers more often. That is true especially for the life science and health science disciplines. Ms. Corbyn from Nature News saved me the need to summarize the paper by writing an excellent article about it.

Based on their findings, Bornmann et al. suggested to concentrate funding on already highly-cited researchers and research groups ("A concentration of resources on these elite structures seems to be practical especially for the life sciences and health sciences"). This is already happening, to some extent, but if the authors' offer is to be accepted, I suspect highly-cited authors will forever remain at the top, simply because they will get most of the funding.

Now, citations don't exist in a social vacuum; despite the tendency to see them as "objective" representations of papers which have influenced other scholarly works, they are affected by factors like the paper's publishing journal, personal connections, coverage of the paper in the mass media, and more. Bornmann et al.'s recommendation might cause funding agencies to end up giving their money to the most popular, connected researchers, who are already well-established in their discipline.

Bornmann, L., de Moya Anegón, F., & Leydesdorff, L. (2010). Do Scientific Advancements Lean on the Shoulders of Giants? A Bibliometric Investigation of the Ortega Hypothesis PLOS ONE, 5 (10) : 10.1371/journal.pone.0013327

Tweeting emotions: sentiment in Twitter events

2010-10-19T09:46:00.000-07:00

Thelwall*, Buckley and Paltoglou (it's a preprint of a paper which is going to be published in JASIST soon) studied the emotional responses in 34, 770, 790 Twitter messages, tweeted from February 9 to March 9, 2010. The main two events in the media that month were the Oscars and the Winter Olympics.

They identified the 30 most popular events (biggest spikes of interest) and tried to classify the sentiment strength expressed in the tweets using an algorithm called SentiStrength. SentiStrength was developed for analysis of MySpace comments, which means it is most suitable for analysing, shall we say, English that didn't come straight out of the Oxford dictionary. SentiStrength measures emotions with two 1-5 scales, one for positive sentiment and one for negative.

As far as emotions on Twitter go, important events mean mainly an increase in negativity, with heavier traffic hours having stronger negativity sentiment. Also, hours after the traffic's peak have stronger sentiment than the hours before. There was also a correlation between higher traffic hours and stronger positive sentiment, in comparison with the hours before, but it wasn't as strong as the correlations found for negative sentiment.

The authors conclude that "important events in Twitter are associated with increases in average negative sentiment strength".

Increase in negative sentiment strength doesn't always say a decrease in positive sentiment, because people can see an event from various view points (is Sandra Bullock winning the Oscar good or bad? Depends on the person asked).

Unfortunately, the authors weren't able to identify the importance of an event from the strength of the expressed emotions. While statistically significant, the changes in emotion strength related to popular events were only around 1% and "were far from universal". The authors' conclusion was that tweeting about events is less about emotional "gut" reactions than about "affording posters opportunities to satisfy personal goals" (say, making a joke).

Thelwall, M., Buckley, K., & Paltoglou, G (2010). Sentiment in Twitter events JASIST

*same disclosure as last post.

When is webometrics most useful?

2010-10-05T18:43:00.000-07:00

Like many terms in Information Science (including 'Information Science' itself) the term 'webometrics' is pretty vague. Björneborn and Ingwersen (2004) defined webometrics as "the study of the quantitative aspects of the construction and use of information resources, structures and technologies on the Web drawing on bibliometric and informetric approaches." I guess this definition will have to do for the time being.

Thelwall*, Klitkou, Verbeek, Stuart and Vincent (2010) set out to find in which fields webometrics is most effective. The result is quite a long paper, that I'm going to be very general about its conclusions. As expected, webometrics doesn't have the same effectiveness in every field. It is at its best with emerging and/or "hot" fields. That is because web publication is easier and faster than publication in traditional scientific outlets, and researchers can publish ongoing results with little delay.

In some disciplines plenty of their products aren't regularly published in journals (social sciences, humanities, applied fields, etc.) and therefore aren't as well-covered by bibliometrical databases as disciplines with a journal-publishing culture. Bibliometrics is also bound to have a poor coverage of multidisciplinary fields, because their outputs are published in various outlets and are often cited in different manners.

In general, webometrics analysis gives better results in fields with standards and/or norms for web publishing, but the results might not be reliable in fields where a small number of research groups and their projects (databases, web portals and so on) have a disproportional web presence.

Collaborations are often better caught in webometric analysis, since not all collaborative works have "official" outputs.

Webometrics works better for smaller fields. It's harder to get a complete picture of large fields with current methods.

Last but not least: webometric analysis is usually faster and cheaper than bibliometric one.

Thelwall and his colleagues concluded that "whilst webometrics is still inferior to bibliometrics for most purposes it seems that it has advantages for some types of field, particularly new, small fields, and can deliver policy-relevant (process) indicators to promote effective collaboration and communication," (in short: use with caution).

Appropriate disclosure: Prof. Thelwall is one of my dissertation advisors . My favorite from his long list of achievements is that he managed to publish a serious research paper including a YouTube cat video.

Thelwall, M., Klitkou, A., Verbeek, A., Stuart, D., & Vincent, C. (2010). Policy-relevant Webometrics for individual scientific fields Journal of the American Society for Information Science and Technology, 61 (7), 1464-1475 DOI: 10.1002/asi.21345

Authorities and hubs in Twitter conference feeds

2010-10-03T16:31:00.000-07:00

"Understanding how Twitter is used to spread scientific messages" is another conference paper studying the scientific uses of Twitter.

Letierce, Passant, Breslin and Decker (2010) analysed Twitter feeds from the International Semantic Web Conference (#iswc2009), the Online Information Conference 2009 (#online09) and the European Semantic Technology Conference (#estc2009). First, they checked the distribution of tweets per user, then the distribution of tweets that were directed to individuals (@user messages). They found that both were Power Law distributions.

After that, they used the HITS (Hyperlink-Induced Topic Search) algorithm to determine the hubs and authorities of the conference feeds. Users who addressed many @user messages were considered hubs, while the users who received many @user tweets were considered authorities. Letierce et al.'s not-very-surprising conclusion was that users with both high hub and authorities scores were often the organizers of the events studied in the research. Also, users with real-world authority (their example was @timberners_lee) also had t-authority. Of course, Letierce and her colleagues couldn't determine if there are more real-world authorities that don't use Twitter (perhaps a content analysis of the tweets can determine if there are talks about people who aren't Twitter users, but that's very time-consuming and not the point of the research here).

In addition, the paper includes a small survey (61 participants) conducted by the authors, but I chose not to discuss it here, because of the small sample.

Letierce, J., Passant, A., Breslin, J., & Decker, S. (2010). Understanding how Twitter is used to spread scientific messages Proceedings of the WebSci10: Extending the Frontiers of Society On-Line, April 26-27th, Raleigh, NC: US.

Hyping Astronomy

2010-09-30T08:36:00.002-07:00

Astronomers from the Carnegie Institution and the University of California, Santa Cruz, have discovered and earth-sized planet called Gilese 581. It's 20 light-years away, which makes it an unlikely traveling destination, but this is exciting news nonetheless.

The abstract is enthusiastic yet cautions, saying that:

"The estimated equilibrium temperature of GJ 581g is 228 K, placing it squarely in the middle of the habitable zone of the star and offering a very compelling case for a potentially habitable planet around a very nearby star."

The press release is about the same, emphasizing the potential habitability of the planet, how hard it was to locate it and explains a bit about radial velocity. It more-or-less follows the rules I mentioned in a previous post.

The news, however, say: "Odds of life on nearby planet '100 percent,' astronomer says." (Fox News and others).

What went wrong? Where did the over-hyping come from? Unfortunately, Prof. Steven Vogt, one of the discoverers, told AP that "We don't have any direct way to sense that there's life there, my own personal opinion is that it is hard to imagine that life has not taken a foothold there."

He also said: "Personally, given the ubiquity and propensity of life to flourish wherever it can, I would say that the chances for life on this planet are 100 percent. I have almost no doubt about it."

It went downhill from there.

So, we have a scientist hyping his findings, and media all-to-ready to hype it. The results are false (or at least unverified) headlines.

(video: Steven Vogt talking to AP)

Hat tip: Yoav Landsman (Hebrew)

Vogt, S. S., Butler, P. R., Rivera, E. J., Haghighipour, N., Henry, G. W., & Williamson, M. H. (2010). The Lick-Carnegie Exoplanet Survey: A 3.1 M_Earth Planet in the Habitable Zone of the Nearby M3V Star Gliese 581 Arxiv : 1009.5733v1

Citing in 140 characters

2010-09-28T14:26:00.000-07:00

Using the Israeli SF&F society's time machine* I managed to get an advanced copy of Priem and Costello's paper: "How and why scholars cite on Twitter", which will be presented at the ASIST 2010 conference (22-27 October). As one can learn from the paper's name, it deals with researchers' Twitter citing behavior.

The snowball sampling here is a bit problematic, as the authors themselves admit in the conclusion part. They started with 3 academics from different disciplines, asked them to tweet about the research, and asked new participants to tweet about the research as well. They ended up with 28 academics (faculty, post-docs and Ph.D students).

They took a mixed-method approach, both interviewing the participants and harvesting their tweets. They sampled each participant's last hundred tweets and their final sample included 2,322 tweets containing hyperlinks.

Citations here were defined as "direct or indirect links from a tweet to a peer-reviewed scholarly research online". The citations were divided to direct citations (tweets which led straight to the academic resource) and indirect citations (there's another web page between the tweet and the academic resource). 6% of the tweets in the sample contained citations. A bit more than half (52%) of those citations were direct and the rest were indirect.

Main conclusions

One of the reasons for indirect t-citings is the nonavailability of the academic resource itself. Instead of linking to a pay-walled paper, the link can be to a blog post discussing the paper.
T-citings are considered part of an ongoing conversation between colleagues and are part of the researcher's workflow.
Unlike most citings in traditional academic discourse, t-citings aren't usually used to support an argument, but to filter information. A t-citing can often be considered a recommendation for the resource in question.
T-citings are faster than a speeding bullet. 15% of the t-citings were tweeted at the publishing day of the papers they referred to, and 39% of the t-citings were made within a week of the paper's publication.

This is the first study I've read about Twitter citings and I believe the authors did a good job in capturing the "water-cooler" essence of t-citings. A bigger sample might allow to study the differences between the t-citing habits of researchers from different disciplines.

*Okay, I emailed the authors.

Priem, J., & Costello K. L. (2010). How and why scholars cite on Twitter ASIST, Oct. 22-27, Pittsburgh, PA, USA.

It's not what you publish, it's where you publish it

2010-09-25T10:55:00.000-07:00

Last post I mentioned the Matthew Effect, or "The rich get richer." In Bibliometrics, it means that the more you're cited and/or the more you publish, the more you'll continue to get cited/publish. When applied to journals, that means that papers published in high-impact journals get cited more often. As a result, the IF of the journals remains high, and so on. In short, a positive feedback loop.

However, there's always a question of quality. Perhaps the papers published in high-impact journals are, indeed, better? Lariviere and Gingras (2010) tried to solve the problem by using duplicates: the same paper published twice, in a high IF journal and in a low IF journal. In order to find those papers, they searched the WoS database, comparing papers according to their names, first authors and the number of cited references. Out of 4,918 pairs of papers identified they ended up using 4,532. The publication year of the pairs was either identical of in the one year range in about 80% of the papers.

They compared the average numbers of citations and average of relative citations for disciplines with more than 30 duplicates. The biggest Matthew Effect was found in the clinical medicine (21.46 for high IF, 12.08 for low IF) and Biomedical Research. (19.77 and 8.15). Significant differences were also found for Chemistry, Engineering and Technology, Physics and Social Sciences. However, there weren’t significant differences for Biology, Earth and Space, Health (Social Sciences), Math and Psychology.

Personally, I wonder if part of the effect can be accounted for the pay walls: libraries tend to buy more subscriptions to high-impact journals, so the chances of getting access to a paper in one of those journals is higher.

Speaking of the Matthew Effect, John Wilbanks, vice president of science at Creative Commons, just published a short article in Seed Magazine about the subject. He points out that in 1968 (the year Merton named the “Matthew Effect”) “the average age of a biomedical researcher in the US receiving his or her first significant funding was 35 or younger.” Today, it’s almost 42 for NIH grants. That means that fewer young, talented scientists get opportunities for independent research, while the already established scientists get even more funding.

Wilbanks recommends that we “start rethinking the way we reward and fund science and assess researchers using more than just citations.”

All I can say, Mr. Wilbanks, is that Bibliometricans are working on it…

P.S. Of course, as soon as I finished this post I ran into this post in The Scholarly Kitchen about the very same paper. Oh, well.

Lariviere, V. & Gingras, Y. (2010). The impact factor’s Matthew effect: a natural experiment in bibliometrics Journal of the American Society for Information Science and Technology, 2 (61), 424-427 : 10.1002/asi.21232

The citation game

2010-09-22T06:26:00.000-07:00

Although "Publish or perish" is more catchy, I believe it should be "Get cited or perish". Why? Because many people (without naming names, we're talking about your promotion committee)also rely on citation data when deciding a scientist's future.

While citations often correlate with other measurements of scientific influence (awards, research grants, etc.) citations are hardly objective, and depend on more factors than someone finding your work useful.

Time-dependent factors: Recent publications are more likely to get cited than older ones.

The Matthew effect: "The rich get richer and the poor get poorer." The name was given by Merton (1968) who based it upon the Gospel of Matthew:

"For to all those who have, more will be given, and they will have an abundance; but from those who have nothing, even what they have will be taken away."
—Matthew 25:29, New Revised Standard Version.

What it means is that the more cited a paper is, the more it will continue to get cited. Works for famous scientists as well.

Field-dependent factors: Your chances for citing go up when you work in a bigger field with more publications and vice-versa.

Journal-dependent factors: Getting published in a high-factor journal doesn't necessarily mean your paper is the best thing since sliced bread, but it means more people are likely to think so. Also, the first paper in a journal usually gets cited more often (I wonder if that's still relevant, given how wide-spread electronic access is these days).

Paper-dependent factors: The frequency of citations for the paper correlates positively with the number of co-authors and the length of the reference list. Cite more, get cited more.

Longer papers get cited more often than shorter ones, simply because they have more content.

Author/reader dependent factors: Developing a good social network with colleagues can get you cited more often.

Availability of publication: Do people have access to your paper? Open Access papers get cited more often (given that many universities' policy regarding paid subscriptions is "NOT", that's hardly surprising).

Technical problems: Errors in the citing of your paper may prevent the citing from counting when a paper's references list is analysed. Another important rule is to pick one form of your name and stick to it (if you're John Smith, don't start being John K. Smith all of a sudden).

Above all, write a good paper (it can't hurt).

An important note: most of the material in this post is from Bornmann and Daniel's excellent review (2008).

Bornmann, L., & Daniel, H. (2008). What do citation counts measure? A review of studies on citing behavior Journal of Documentation, 64 (1), 45-80 DOI: 10.1108/00220410810844150

Eysenbach, G. (2006). Citation Advantage of Open Access Articles PLoS Biology, 4 (5) DOI: 10.1371/journal.pbio.0040157

Peer review, the faster version, part II

2010-09-20T09:16:00.000-07:00

I mentioned here that there was an unofficial peer-review process going concerning the mathematical claim by Dr. Vinay Deolalikar that P does not equal NP. In this video, mathematicians Ken Clarkson, Ron Fagin and Ryan Williams explain why they think Deolalikar's is wrong.

Other than that, Ken Clarkson also shows the timeline of the peer-review process that happened in the web and how fast it was, compared with the time it took to find flaws in proofs in the past.

Watch live streaming video from newintelligence at livestream.com

Don't say you found aliens (unless you actually have)

2010-09-18T12:48:00.000-07:00

Unlike with health and medicine press releases (Woloshin and Schwartz have a few good papers about the matter) I haven't seen much research about other scientific press release. That's why I was glad to find the paper "Credibility of science communication: An exploratory study of astronomy press releases" by Nielsen et al. (2007).

They conducted 11 in-depth interviews with journalists, scientists and public information officers, and came up with several conclusions regarding the accuracy and credibility of astronomy press releases.

Credibility was defined by the interviewees as "being honest and doing your homework." Hype was defined as overstating the importance of results in order to increase visibility.

Credibility problems with press releases

Problems were usually caused by either the press release trying to make the issuing institution look better, or trying to make other institutions look worse.

The level of communication effort: finding some well-known person to tell the media how much the research described in the press release is significant to science.
The wording of the press release: even if it is possible you found alien life, keep that question mark at the end of "Alien life found?".
Dictating the timing of a press release: we just happened to discover something really important, just in time for the annual budget meeting! Other time-related sins are publishing the press release before the peer-review paper is out, and timing the release to screw up the competition's own press release or event.
Omission of reference to other scientists' work: this isn't the 17th century. It is hardly likely you did everything by yourself, or haven't built on some previous research.
Unjust comparison with other facilities.

Good ways to avoid lack of credibility (which can be in science, unlike in politics, problematic) is to have internal referees to the press release before its publication. Also, the importance of a peer-reviewed paper backing the press release can't be overstated.

Despited everything said here, the authors' overall conclusion is that "...credibility problems for astronomy press release do not exist, though examples certainly exist."

I find this conclusion very encouraging.

Nielsen, L. H., Torpe Jørgensen, N., Jantzen, K., & Christensen, L. L. (2007). Credibility of science communication: An exploratory study of astronomy press releases Proceedings from the IAU/National Observatory of Athens/ESA/ESO Conference, Athens, Greece.

In which I flog a dead horse

2010-09-13T11:07:00.001-07:00

In this post I'd like to revisit the Kouper paper (2010) and even more important, the way it was accepted among science bloggers.

First of all, let's start with the blogs studied. The paper says that "The blogs were sampled via the Internet search for "science blogs" and "blogs about science" and by following scientific news on the moment of data collection in Summer, 2008". I'm not sure why Ms. Kouper felt the need to make both searches because Uncle Google, bless its PageRank heart, gives, as expected, very similar results for both searches (and an Information Science student should know that). This kind of sampling means the blogs studied will probably be the most popular at the time, which is indeed what happened. Pharyngula and The Panda Thumb aren't typical science blogs.

Also, putting all the blogs in the research under one category is, in my opinion, wrong. One-person-blog isn't the same as Wired Science with its many writers. As A Blog Around the Clock puts it: "Wired Science is a blog owned by a media company.

There's little wonder that Kouper's first conclusion was "Science blogs examined in this study are very heterogeneous." I believe an effort should have been made, at least, to categorize the blogs in a way that won't compare apples and oranges.

A Blog Around the Clock does us a great service by revealing the doubts the blogger had about the paper, as a peer-reviewer, during the peer-review process. He criticizes the methodology (the small sample, the cut-off for the comments' content analysis at 15 comments) and the conclusions. Kouper's main conclusion was that: "It appears that science blogging can also be characterized as relying on reductive analysis and dependent reporting and drawing caustic and petty commentary."

Perhaps the biggest problem of the paper is that the author expect science blogs and science bloggers to fit her ideas of the ways to engage the public in science. She thinks, for example, that “An interesting practical experiment would also be to reverse the roles of writers and readers and invite the so called “ordinary persons” to create and publish science blogs, i.e., to engage them in the practices of science blog writing rather than reading or commenting."

To which The Panda's Thumb answered: "Hm? Why would that be interesting? And, for that matter, “ordinary persons” have the same access to blogging software as do scientists; nothing (except disinclination or disinterest) is stopping “ordinary persons” from blogging about anything they wish."

It seems that Kouper sees science blogging as some sort of elitist activity, while I believe it is more of a meritocracy. If you want to blog about science, write well, and blog consistently, people will read you (though it might take a while).

As opposed to Kouper, Kjellberg (2010) took a different approach to science blogging, by conducting 12 in-depth interviews with science bloggers who are also active researchers. I further discuss the paper here. Kjellberg's paper deals with less famous blogs and bloggers (and most of the blogs are in Swedish) , which could be part of the reason it hasn't gotten any attention from the blogosphere, as far as I can tell.

The main reason I think it has gone unnoticed (so far) is that it isn't controversial enough. It fits more with the "storybook image" of science, as Cronin (1984) called it. Blog posts which say "I agree with the paper", attract less attention than controversial blog posts. As Goodell (1977) said, "The famous scientist is controversial."

ETA: I'd like to thank Neuroskeptic for insight. I've edited a certain sentence so it reflects reality more accurately.

Kouper, I. (2010). Science blogs and public engagement with science: practices, challenges, and opportunities Jcom, 9 (1)

Kjellberg, S. (2010). I am a blogging researcher: Motivations for blogging in a scholarly context First Monday, 15 (8)

Goodell, R. (1977). The visible scientists. Boston : Little, Brown ISBN: 0316320005

Cronin, B. (1984). The Citation Process: The Role and Significance of Citations in Scientific Communication London: Taylor Graham Publishing

The Famous Scientist

2010-09-09T09:17:00.001-07:00

What makes a scientist famous?

Rae Goodell (Later known as Simpson), in her dissertation-turned-book, "The Visible Scientists" studied the visible scientists of the seventies (Sagan, Skinner, Mead, etc.). Her book summarizes the essentials of being a famous scientist.

The hardest to achieve is a credible reputation. The visible scientist is an authority. A well-known institution is a must (Harvard/Stanford/Any IV League university).
A "Hot Topic". Back in the seventies people talked about the population explosion and aliens, today evolution and/or global warming will do the job.
Be Controversial. Professor Dawkins is doing it right.
Have a colorful image (don't be dull). Paul Ehrlich, for example, had a sterilization operation.
Be Articulate. Be quotable ("Give your child an IUD to take to 'Show and Tell'"- Paul Ehrlich).

The most important factor of being a visible scientist in the seventies was, of course, appearing in Johnny Carson's "Tonight" show. Once a scientist was featured in that show, the way to become an "Anything Authority", as Arthur Herzog put it in the The B.S. Factor, was short.

Goodell, R. (1977). The visible scientists. Boston : Little, Brown ISBN: 0316320005

Some Science Blogging Meta

2010-09-05T18:47:00.001-07:00

I love the Groth and Gurney (2010) research, and not just because it introduced me to http://researchblogging.org/. The authors analyzed 295 blog posts about chemistry and the included citations. In comparison to the usual pieces which deal with science blogging in the scholarly literature, this paper has dealt with a large number of posts.

Most of what I've read about science blogging are either opinion articles (Batts et al, 2008), or qualitative research, aka interviews with a small number of bloggers the authors deem important (Amsen, 2006; Kjellberg, 2010). Mind you, there's nothing wrong with those - in fact, they make a fascinating reading - but every now and then a girl needs some good, solid numbers to put in her literature review. Yes, I'm aware of the Kouper paper, but its methodological flaws have already been discussed extensively.

But back to the Groth and Gurney paper. They have found, as expected, that most papers were published in the same year as the blog posts discussing them (table taken from the paper), which, of course, shows one of the main advantages of blogs over traditional scientific literature: They're as current as your last breath.

They have also found that "scientific discourse on the Web focuses on high quality science", based on their finding that 70.5% of the citations came from high-impact journals.

Strictly speaking, it's wrong to judge a paper by its journal, but I didn't expect them to evaluate 300 papers on their own. Terribly time-consuming. So, the IFs of the journals are used as approximations.

There's more, of course, but I won't deal with the rest in this post. I hope that Groth and Gurney will expand their research to other disciplines in the future.

Groth, P. & Gurney, T. (2010). Studying Scientific Discourse on the Web Using

Bibliometrics: A Chemistry Blogging Case Study In press

Kjellberg, S. (2010). I am a blogging researcher: Motivations for blogging in a scholarly context First Monday, 15 (8)

Amsen, A. (2006). Who benefits from science blogging? Hypothesis (4)

Kouper, I. (2010). Science blogs and public engagement with science: practices, challenges, and opportunities. Journal of Science Communication, 9 (1)

Batts, S. A., Anthis, N. J. & Smith, T. C. (2008). Advancing Science through Conversations: Bridging the Gap between Blogs and the Academy. PLoS Biology, 6 (9) DOI: 10.1371/journal.pbio.0060240

The Volokh, the slashdot and the NYT effects

2010-09-01T20:19:00.000-07:00

Back in 2007, Paul Ohm, a law professor in the University of Colorado law school, guest-blogged in a popular law blog called The Volokh Conspiracy. He guest-blogged for one week about two of his papers: "The Analog Hole and the Price of Music: An Empirical Study" and "The Myth of the Superuser: Fear, Risk, and Harm Online." Being more computer-savvy than the average law professor (he has a B.Sc. in Computer Science) he wrote a script which checked the number of abstract views and downloads of his papers from the Social Science Research Network (SSRN). Both have gone up. Then his posts were linked to by Slashdot, and the numbers went up even more (graph taken from Professor Ohm's paper).

Currently, "Superuser" has been downloaded 1,434 times and its abstract viewed 8,859 times. The "Analog" paper has been downloaded 412 times and its abstract viewed 2,942 times. According to Google Scholar, "Superuser" has been cited 29 times and "Analog" only five, so there is a certain correlation (which I admit I didn't calculate) between downloads and views in SSRN and citations (assuming GS' citation count is more-or-less accurate. Do that as your own risk).

But that's not the entire story. Looking through Ohm's other papers, I've noticed that this paper: "Broken Promises of Privacy: Responding to the Surprising Failure of Anonymization" has been downloaded 5,827 times and its abstract viewed 22,528 times, even though it was only published last year. A quick Google search brought up the possible reason: the paper has been mentioned in a New York Times blog, as well as in this site. It has also been cited at least 4 times (GS is a bit confusing because it presents two entries for this paper).Naturally, there are many more variants at work here (for example, the subject of the paper) but I think this is a demonstration of the power of central, as opposed to niche blogs and sites.

Paul Ohm (2007). Do Blogs Influence SSRN Downloads? Empirically Testing the Volokh and Slashdot Effects U of Colorado Law Legal Studies Research Paper

The Citation as a Meme

2010-08-28T19:01:00.000-07:00

Weinstock (1971, quoted in Cronin, 1984. Cronin's The Citation Process is an awesome book, go read) listed 15 functions of citations. The first on the list is "Paying homage to pioneers," and number 12 is "Identifying original publications in which an idea or concept was discussed." In short, citing classical papers.

For example, even though it has been published in 1953, Watson and Crick's DNA paper is still being cited. That, of course, does not mean it is actually being read. The DNA structure is now a part of every Biology 101 curriculum, but I'll be very surprised if more than a handful of the people studying it in the last decades have read the original paper.

Yet, the paper is still being cited. Same with other famous papers, books, etc. The classical paper citation has become an entity of its own, having been detached from The Paper. The Paper has been reduced from a meme complex to a single meme which carries on and on.

So, citation of a classic paper, especially an on old one, is usually more of "I know what those guys did and I appreciate it" than "I've read the paper and picked up something useful."

I really need to hand those out with my Meidaat paper

2010-08-26T06:24:00.000-07:00

My thesis dealt with Ynet and NRG health reporting, and soon enough (September) the journal Meidaat (Hebrew, unfortunately) is about to publish a paper based on said thesis. These labels are more than appropriate...

(source).

Most of the papers reported (two-thirds in Ynet, three-quarters in NRG) did appear in a peer-review journal, but I doubt the "journalists" actually read them.

My favorite finding of all times was a sentence with a word misspelled in a hospital press release that appeared, intact, in a Ynet article. Invest in a good spell checker (and in good science reporting...). It was one of those researches that *didn't* come from a peer-reviewed journal.

Scientometrics 2.0, part I

2010-08-23T14:54:00.000-07:00

Today we're going to discuss this paper, by Priem and Hemminger (2010), dealing with Scientometrics (a general name for Bibliometrics, Webometrics, Influmetrics, and all sorts of other metrics regarding scientific activity). But, before we start, I want to protest First Monday's terrible references format. Sure, it looks fine in-text, with the last name and the year, but at the reference list the references start with the first letter of the author's first name! How am I supposed to know the author's first name? Only Darwin knows.

Anyway, Priem and Hemminger offer a state-of-the-art review of Web 2.0 tools that can be mined for scholarly data. They suggest seven categories of tools, of which I'm only going to mention four in this post.

1. Microblogging - Microblogging means Twitter. Twitter is used by scientists, among others, to discuss papers and conferences. From my experience, many people tweet from conferences under the conference hashtag.

2. Social Bookmarking - Social bookmarking services like Delicious, Connotea and CiteULike can be mined and show scientific trends by pointing out the popular papers bookmarked and popular tags.

3. Wikipedia - Wikipedia is popular among students and faculty as a starting point for basic knowledge. For other web users, Wikipedia is often their only knowledge source. So, papers cited in Wikipedia are more likely to have public impact. Indeed, the JCR and Wikipedia citations correlate well.

4. Blogging - By now, blogs are well- established in the web culture. Many scientists, Fields Medalists included, maintain scholarly blogs. When discussing academic papers, those scientists often cite their sources in traditional manner. Excellent examples are posts aggregated by the Research Blogging service.

That's it for today. The next part will discuss other categories of Web 2.0 services with possible scholarly use.

The Impact Factor

2010-08-20T16:50:00.000-07:00

To use the Wikipedia's definition, Impact Factor is "a measure reflecting the average number of citations to articles published in science and social science journals." This innocent definition hides underneath it a world of problems, which means the IF should be used with caution. For example, many journals publish non- research papers (commentaries, opinions, etc.). If those get cited, the citation is added to the journal's citation count, but the number of papers remains the same. So, journals who don't publish this sort of articles are at disadvantage in comparison with those who do.

Even in a high-impact journal, papers don't necessarily have the same quality. So, being published in a high-impact journal doesn't automatically mean the paper has a larger impact than those in the less known journals.

The quality of a paper isn't the only factor influencing its citing. Papers in Open Access journals get, on average, more frequently cited than those behind a pay wall.

There is also the time factor - the IF is generally calculated for the two previous years. That means that if a paper is a "late bloomer" and only get cited after that time period, those citations won't be represented in the publishing journal's IF.

A good introduction to the subject is this paper (published in Retrovirology, of all places).

Information Hub Blogs

2010-08-19T15:28:00.000-07:00

Information Hub Blogs (unfortunately behind a pay wall) is a relatively old paper by my own prof, Judit Bar-Ilan. The paper content-analyses a set of 15 professional blogs in computer, library and information science. What's especially good about this paper is that is has an excellent literature review about the definition of blogs and the categories they can be classified into (by authorship, content, style...).

The conclusion is that these blogs act as filters and concentrate relevant information ("one stop information kiosks or information hubs"). These blogs are meant to disseminate professional information, as opposed to personal blogs, and rarely deal with the author's private life.

Peer review, the faster version

2010-08-16T11:40:00.000-07:00

About a week ago Dr. Vinay Deolalikar, a researcher at HP labs published what he claims to be the solution to the P versus NP problem. It is one of the Millennium Prize Problems, and there's a one-million-dollar award waiting to whoever solves it. While I'll be the first to admit I have no idea if the solution (P doesn't equal NP) is true, there's an unofficial peer-review process going on over here.

More to come! (credit goes to my advisor for noticing the process).

Why do scientists blog?

2010-08-14T10:51:00.000-07:00

Today I'm going to discuss a paper by Sara Kjellberg, a PhD student from Lund University, Sweden. Ms Kjellberg interviewed 12 science bloggers about their blogging practices and motivations, as well as the functions of their blogs. She found that there are six main functions: disseminating content, expressing opinions, keeping up–to–date and remembering, writing, interacting, and creating relationships.

Disseminating content: science bloggers are usually passionate about their field of research, and the blog is a way for them to disseminate knowledge to a larger audience and in less formal manner than in scholarly journals. Interesting, though, that despite the will to reach the public, the interviewed researchers wanted to make their blogs more scholarly-like by using references.

Expressing Opinions: Unlike the "pure" scholarly communication, blogs are meant to be written with a personal touch, and provide the researchers to share their own point of view.

Keeping up-to-date and Remembering: A blog seem to be a perfect 'excuse' for researchers to make the effort and read the newest papers in their field, in order to find material for their own blog posts. Some researchers considered the blog a notebook of a sort, a way to organize their thoughts and ideas.

Writing: The blog is often use as a way to naturally improve one's writing skills.

Interacting: Unfortunately, science bloggers that aren't PZ Myers (Pharyngula) normally don't have a wide audience. Most science blogs are used as kind of 'seminars' for a small group of people to change ideas around a blog posting. In other cases, the readers rarely interact with the bloggers.

Creating Relationships: Blogging is a way to become part of scientific networks that aren't usually present in the blogger's day-to-day life.