Disciplinary Differences in Twitter Scholarly Communication


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This paper investigates disciplinary differences in how researchers use the microblogging site Twitter. Tweets from researchers in five disciplines (astrophysics, biochemistry, digital humanities, economics, and history of science) were collected and analyzed both statistically and qualitatively. The results suggest that researchers tend to share more links and retweet more than the average Twitter users in earlier research. The results also suggest that there are clear disciplinary differences in how researchers use Twitter. Biochemists retweet substantially more than researchers in the other disciplines. Researchers in digital humanities use Twitter more for conversations, while researchers in economics share more links than other researchers. The results also suggest that researchers in biochemistry, astrophysics and digital humanities are using Twitter for scholarly communication, while scientific use of Twitter in economics and history of science is marginal.

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Disciplinary Differences in Twitter Scholarly Communication

  1. 1. Disciplinary Differences in Twitter Scholarly Communication Kim Holmberg1 and Mike Thelwall2 1 k.holmberg@wlv.ac.uk, http://kimholmberg.fi | 2 m.thelwall@wlv.ac.uk School of Technology, University of Wolverhampton, UK ISSI 2013, Vienna, Austria, 17/7/13
  2. 2. Cascades, Islands, or Streams? Time, Topic, and Scholarly Activities in Humanities and Social Science Research Indiana University, Bloomington, USA University of Wolverhampton, UK Université de Montréal, Canada
  3. 3. Cascades, Islands, or Streams? Integrate several datasets representing a broad range of scholarly activities Use methodological and data triangulation to explore the lifecycle of topics within and across a range of scholarly activities Develop transparent tools and techniques to enable future predictive analyses
  4. 4. #Altmetrics is the study and use of non- traditional scholarly impact measures that are based on activity in web-based environments. http://www.ploscollections.org/article/browse/issue/info%3Adoi%2F10.1371%2Fissue.pcol.v02.i19;jsessionid=70DF7B9AD8D7CE819F666E7791D4084E
  5. 5. This research investigates how researchers in different disciplines use Twitter for scholarly communication with the following research questions: 1. What do researchers typically tweet about? 2. Are there disciplinary differences in the types of tweet sent by researchers?
  6. 6. Tweet Retweet or RT @username Message (privat) #Hashtag
  7. 7. Discipline Researchers Tweets1 Tweets per researcher Astrophysics 45 59,742 1,328 Biochemistry 45 40,128 892 Digital humanities 51 89,106 1,747 Economics 45 57,673 1,282 History of science 42 58,414 1,391 Data was collected between 4 March 2012 and 16 October 2012 using Twitter’s API (with http://lexiurl.wlv.ac.uk/) DATA 1) Twitter restricts the collection of tweets sent by users to approx. 3,200 tweets per username
  8. 8. METHODS From each discipline a random sample of 200 tweets were classified by the first author using a multifaceted classification scheme. Of these 25% were coded by another researcher. In facet 1 the communication style was classified and in facet 2 the scientific content, or lack of it, was classified.
  9. 9. FACET 1communication style • Retweets were identified by the acronym RT or by some other way that clearly indicated that the tweet was at least a partial copy of a previous tweet. • Conversational tweets were identified by @-sign followed by a username and were not retweets. • Tweets in the Links category were tweets that were neither retweets nor conversational tweets but contained one or more URLs. • Other- all remaining tweets.
  10. 10. FACET 2content • The scholarly communication category contained tweets that were clearly about research-related communication. • Discipline-relevant tweets were clearly about the discipline but not directly research related. • Not clear was for tweets with no clear topic. The topic of the tweets and the scientific content were unclear. • Not about science and not about the discipline. Tweets irrelevant to the discipline and research. A conservative approach was taken in the coding
  11. 11. RESULTS Figure 1. Types of tweets by discipline (facet 1) 23.5 42 22 24.5 25 31.5 16.5 38 16 28.5 23.5 21.5 15.5 38 27 21.5 20 24.5 21.5 19.5 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Astrophysics Biochemistry Digital humanities Economics History of science Other Links Conversations Retweets Intercoder agreement in facet 1 was 99.2%
  12. 12. RESULTS Figure 2. Scientific content of the tweets by discipline (facet 2) 23 33.5 22 6.5 7.5 22 13.5 12.5 51.5 8.5 25.5 24 31.5 16 26.5 29.5 29 34 26 57.5 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Astrophysics Biochemistry Digital humanities Economics History of science Clearly not science Not clear Discipline relevant Scholarly communication Intercoder agreement in facet 2 was 68.9% and 0.587 with Cohen’s Kappa.
  13. 13. RESULTS Figure 3. Scientific content of the tweets by communication type 6.5 18 8.5 1 1 3 3.5 3 0 0.5 10 7 3 5 4.5 3.5 5 7.5 0.5 1.5 0% 5% 10% 15% 20% 25% 30% 35% 40% Astrophysics Biochemistry Digital humanities Economics History of science Other Links Conversations Retweets
  14. 14. LIMITATIONS • The sample is based upon 42-51 researchers per discipline  The disciplinary differences found may be due to the sample of researchers rather than their disciplines. • It may be easier to classify tweets in some disciplines  Some disciplines have more specialist vocabularies (e.g., astrophysics) and others discuss issues that are of general interest to society (e.g., economics).  While facet 1 is fairly straightforward, facet 2 was classified conservatively so that clear evidence was needed for the more scholarly categories.
  15. 15. CONCLUSIONS The results suggest that researchers tend to share more links and retweet more than the average Twitter users in some earlier research. The results suggests that there may be significant differences between disciplines in the extent to which their active users use Twitter for scholarly communication. It seems to be worrying (?) that some disciplines are avoiding Twitter almost completely for scholarly communication despite other disciplines evidently finding it useful for this purpose.
  16. 16. FUTURE Comparisons between active and not-so-active Twitter users and closer analysis of tweeting behavior. Deeper analysis of the scientific tweets and possible relationships between the tweets and citations. Survey about the researchers’ own thoughts about how they use and what they think about Twitter.
  17. 17. Kim Holmberg Statistical Cybermetrics Research Group University of Wolverhampton, UK K.Holmberg@wlv.ac.uk http://kimholmberg.fi @kholmber Acknowledgements This manuscript is based upon work supported by the international funding initiative Digging into Data. Specifically, funding comes from the National Science Foundation in the United States (Grant No. 1208804), JISC in the United Kingdom, and the Social Sciences and Humanities Research Council of Canada. Danke für Ihre Aufmerksamkeit Slides will be available at