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Disciplinary Differences in Selected Scholars'
Twitter TransmissionsKim Holmberg1 and Mike Thelwall2
1 [email protected], http://kimholmberg.fi | 2 [email protected] School of Technology, University of Wolverhampton, UK
AEW 5/6/13
Cascades, Islands, or Streams? Time, Topic, and Scholarly Activities in
Humanities and Social Science Research
Indiana University, Bloomington, USAUniversity of Wolverhampton, UKUniversité de Montréal, Canada
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
#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
RQThis research investigates how researchers in different disciplines use Twitter for scholarly communication with the following research questions:1. How are researchers in different disciplines using
Twitter for scholarly communication?2. What kinds of disciplinary differences are there in
the use of Twitter for scholarly communication?
TweetRetweet or RT@usernameMessage (privat)#Hashtag
Discipline Researchers Tweets1 Tweets per researcher
Cheminformatics 48 81,836 1,705
Cognitive science 52 50,128 964
Drug discovery 24 18,293 762
Social network analysis 47 41,464 882
Sociology 48 64,447 1,371
Data was collected between 4 March 2012 and 16 October 2012 using Twitter’s API.
DATA
1) Twitter restricts the collection of tweets sent by users to approx. 3,200 tweets
METHODSFrom each discipline a random sample of 200 tweets was selected and these were classified using a multifaceted classification scheme.
In facet 1 the communication style was classified and in facet 2 the scientific content, or lack of it, was classified.
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.
FACET 2content • The scholarly communication category contained tweets that
were clearly about research-related communication. • Discipline-relevant tweets were clearly about disciplinary
communication 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.
RESULTS
Figure 1. Communication styles of the tweets in the five different disciplines
RESULTS
Figure 2. Scientific content of the tweets in the five different disciplines
RESULTS
Figure 3. Scientific content of the tweets by communication type
LIMITATIONS
• Tweets were classified by only one researcher. While facet 1 is fairly straightforward, facet 2 was classified
conservatively so that clear evidence was needed for the more scholarly categories1.
• The sample is based upon 24-52 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., chemoinformatics) and others discuss issues that are of general interest to society (e.g., sociology).
1) In another sample with other disciplines, intercoder agreement in facet 1 was 99.2% and in facet 2 68.9% with Cohen’s Kappa 0.587.
CONCLUSIONS
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.
FUTURE
Comparisons between active and ‘lazy’ Twitter users.
Closer analysis of the scientific tweets and possible relationships between the tweets and citations.
Qualitative study about the researchers’ own thoughts about how they use and what they think about Twitter.
Kim Holmberg, PhDStatistical Cybermetrics Research GroupUniversity of Wolverhampton, [email protected] http://kimholmberg.fi @kholmber
AcknowledgementsThis 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.
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