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Empirical analyses of scientific papers and researchers on Twitter: Results of two studies Stefanie Haustein, Timothy D. Bowman, Kim Holmberg, Vincent.

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Presentation on theme: "Empirical analyses of scientific papers and researchers on Twitter: Results of two studies Stefanie Haustein, Timothy D. Bowman, Kim Holmberg, Vincent."— Presentation transcript:

1 Empirical analyses of scientific papers and researchers on Twitter: Results of two studies Stefanie Haustein, Timothy D. Bowman, Kim Holmberg, Vincent Larivière, Isabella Peters, Cassidy R. Sugimoto, & Mike Thelwall

2 Background when Garfield created SCI, sociologists of science analyzed meaning of publications and citations (Merton, Zuckerman, Cole & Cole, etc.) sociological research What is it to publish a paper? What are the reasons to cite? empirical bibliometric research disciplinary differences in publication and citation behavior delay and obsolescence patterns

3 Background empirical studies helped sociologists to understand structure and norms of science for bibliometricians, studies provided a theoretical framework and legitimation to use citation analysis in research evaluation knowledge about disciplinary differences and obsolescence patterns helped to normalize statistics and create more appropriate indicators

4 Background recently social-media metrics have become important in the scholarly world suggestions to complement (or even replace) citation analysis by so-called ”altmetrics“ broader audience (not just citing authors) more timely however, similar to bibliometrics in the 1960s, little is known about the actual meaning of various social-media counts

5 Research questions What is the relationship between social-media and citation counts? How do various social-media metrics differ? Why are papers tweeted, bookmarked, liked…? Who tweets (bookmarks, likes…) scientific papers? How do these aspects differ across scientific disciplines? Two case studies on Twitter large-scale analysis of tweets of biomedical papers in-depth analysis of astrophysicists on Twitter

6 Aim of the study large-scale analysis of tweets of biomedical papers Twitter coverage Twitter citation rates (tweets per paper) correlation with citations discovering differences between: documents journals disciplines & specialties  providing empirical framework to understand the extent to which biomedical journal articles are tweeted Study I: Tweeting biomedicine Haustein, S., Peters, I., Sugimoto, C.R., Thelwall, M., & Larivière, V. (in press). Tweeting biomedicine: an analysis of tweets and citations in the biomedical literature. Journal of the American Society for Information Science and Technology,

7 Data sets & methods 1.4 million PubMed papers covered by WoS publication years: document types: articles & reviews matching of WoS and PubMed tweet counts collected by Altmetric.com collection based on PMID, DOI, URL matching WoS via PMID journal-based matching of NSF classification tweets per article, Twitter coverage and correlation with citations for: journals NSF disciplines and specialties Study I: Tweeting biomedicine

8 Data sets & methods: framework Study I: Tweeting biomedicine

9 Data sets & methods: correlations Study I: Tweeting biomedicine PY=2010 PY=2011PY=2012

10 Results: documents Study I: Tweeting biomedicine Publication year Twitter coverage Papers (T≥1) Spearman's ρ MeanMedianMaximum T %13, ** C ,922 T %63, ** C ,300 T %57, ** C T %134, ** C ,922 Twitter coverage is quite low but increasing correlation between tweets and citations is very low

11 Results: documents Study I: Tweeting biomedicine ArticleJournalCT Hess et al. (2011). Gain of chromosome band 7q11 in papillary thyroid carcinomas of young patients is associated with exposure to low-dose irradiation PNAS9963 Yasunari et al. (2011). Cesium-137 deposition and contamination of Japanese soils due to the Fukushima nuclear accident PNAS30639 Sparrow et al. (2011). Google Effects on Memory: Cognitive Consequences of Having Information at Our Fingertips Science11558 Onuma et al. (2011). Rebirth of a Dead Belousov–Zhabotinsky Oscillator Journal of Physical Chemistry A Silverberg (2012). Whey protein precipitating moderate to severe acne flares in 5 teenaged athletesCutis--477 Wen et al. (2011). Minimum amount of physical activity for reduced mortality and extended life expectancy: a prospective cohort study Lancet51419 Kramer (2011). Penile Fracture Seems More Likely During Sex Under Stressful Situations Journal of Sexual Medicine Newman & Feldman (2011). Copyright and Open Access at the Bedside New England Journal of Medicine 3332 Reaves et al. (2012). Absence of Detectable Arsenate in DNA from Arsenate-Grown GFAJ-1 CellsScience5323 Bravo et al. (2011). Ingestion of Lactobacillus strain regulates emotional behavior and central GABA receptor expression in a mouse via the vagus nerve PNAS31297 Top 10 tweeted documents: catastrophe & topical / web & social media / curious story scientific discovery / health implication / scholarly community

12 Results: journals 97.7% of 3,812 journals at least tweeted once two-thirds of journals have coverage below 20% and Twitter citation rate < 2.0 high Twitter citation rates often caused by few papers high coverage and Twitter citation rates for general journals Study I: Tweeting biomedicine

13 Results: disciplines Study I: Tweeting biomedicine

14 Results: specialties Study I: Tweeting biomedicine specialties differ in terms of coverage, Twitter citation rate and correlations with citations 47 of 61 specialties show low positive, 3 negative and 13 no correlation bubble size = Twitter citation rate

15 Aim of the study in-depth analysis of astrophysicists on Twitter number of tweets, followers, retweets characteristics of tweets: #hashtags, URLs comparison with scientific output publications citations comparison of tweet and publication content  provide evidence in how far astrophysicists on Twitter use Twitter for scholarly communiation Study II: Astrophysicists on Twitter Haustein, S., Bowman, T.D., Holmberg, K., Larivière, V., & Peters, I., (submitted). Astrophysicists on Twitter: An in-depth analysis of tweeting and scientific publication behavior. Aslib Proceedings.

16 Data sets & methods 37 astrophysicists on Twitter identified by Holmberg & Thelwall (2013) web searches to identify person behind account publications in WoS journals publication years: author disambiguation Twitter account information 68,232 of 289,368 tweets downloaded and analyzed: number of RTs per tweet % of tweets that are RTs % of tweets containing URLs Study II: Astrophysicists on Twitter Holmberg, K., & Thelwall, M. (2013). Disciplinary differences in Twitter scholarly communication. In: Proceedings of ISSI 2013 – 14th International Conference of the International Society for Scientometrics and Informetrics, Vienna, Austria (Vol. 1, pp ).

17 Data sets & methods grouping astrophysicists according to tweeting and publication behavior analyzing differences of tweeting characteristics between user groups Study II: Astrophysicists on Twitter Selected astrophysicists (N=37) tweet rarely ( tweets per day) tweet occasionally ( ) tweet regularly ( ) tweet frequently ( ) total (publishing activity) do not publish (0 publications ) publish occasionally (1-9) publish regularly (14-37) publish frequently (46-112) total (tweeting activity)

18 Data sets & methods comparison of tweet and publication content extraction of noun phrases from tweets and abstracts limited to 18 most frequently publishing astrophysicists to ensure certain number of abstracts analyzing overlap of character strings calculating similarity with cosine per person and overall Study II: Astrophysicists on Twitter Selected astrophysicists (N=37) tweet rarely ( tweets per day) tweet occasionally ( ) tweet regularly ( ) tweet frequently ( ) total (publishing activity) publish regularly (14-37) publish frequently (46-112) total (tweeting activity)

19 Results: correlations comparison of Twitter and publication activity and impact publications and tweets per day: ρ=−0.339* citation rate and tweets per day: ρ=−0.457** citation rate and RT rate: ρ=0.077 Study II: Astrophysicists on Twitter

20 Results: characteristics Study II: Astrophysicists on Twitter Mean share of tweets containing at least one user name or URL per person per group

21 Results: content similarity Study II: Astrophysicists on Twitter overall similarity between abstracts and tweets is low cosine= % of 50,854 tweet NPs in abstracts 16.0% of 12,970 abstract NPs in tweets Twitter coverage among most frequent abstract terms is high, although this differs between users 97,1% of 104 most frequent noun phrases on Twitter

22 Conclusions Twitter coverage of biomedical papers is low but increasing number of tweets per paper varies between journals, disciplines, specialties and from year to year  tweet counts need to be normalized accordingly correlations between tweet and citation counts are low (biomedical papers) or even moderately negative (astrophysicists)  tweets cannot replace citations as measures of scientific impact  challenge is to differentiate between high tweet counts because of value (to scientists and/or the general public) and curiosity

23 Outlook user surveys and qualitative research to investigate who is using scholarly content on social media and why empirical large-scale studies on other metrics

24 Haustein, S., Peters, I., Sugimoto, C.R., Thelwall, M., & Larivière, V. (in press). Tweeting biomedicine: an analysis of tweets and citations in the biomedical literature. Journal of the American Society for Information Science and Technology. Haustein, S., Bowman, T.D., Holmberg, K., Larivière, V., & Peters, I., (submitted). Astrophysicists on Twitter: An in-depth analysis of tweeting and scientific publication behavior. Aslib Proceedings. Stefanie Haustein Thank you for your attention!


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