Beyond Citation Counts - The Potential of Academic Social Network Sites for Scientific Impact Assessment
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Beyond Citation Counts - The Potential of Academic Social Network Sites for Scientific Impact Assessment

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Millions of researchers all around the world have profiles on academic social network sites, such as ResearchGate, Academia.edu, or Mendeley. Still these channels are hardly used for impact......

Millions of researchers all around the world have profiles on academic social network sites, such as ResearchGate, Academia.edu, or Mendeley. Still these channels are hardly used for impact assessment. While scientific impact has traditionally been measured with bibliometrics, social media provide new avenues for influence measurement (Altmetrics). We focus on one specific type of social media, namely academic social network sites. How can such platforms provide insights into scientific impact and add to Altmetrics? To answer this question, we rely on a social network analysis of a research community on ResarchGate. The underlying data was provided by the platform provider. It contains detailed interaction and publication information of 55 faculty members of a Swiss public university. We apply a structural perspective and use centrality measures as core indicators of influence within the network.
Our analysis proceeds in three steps: First, we describe the network structure in terms of classical SNA metrics. Second, we analyze whether researchers’ network centrality is associated with other metrics of influence, namely: (a) activity on the platform (b) traditional metrics of scholarly influence (i.e. mainly bibliographic criteria), and (c) academic position. Third, we compare the network structure with that of participants' co-authorship pattern.
Our findings show that activity on the platform is the best predictor of impact within the network, while publication success and academic play less of a role. Implications for research and practice are provided.

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  • 1. Beyond Citation Counts The Potential of Academic Social Network Sites for Scientific Impact Assessment Christoph Lutz ASNA Conference 2013 Zurich, August 27 2013
  • 2. ASNA Zurich, August 29 2013 Page 2 Executive Summary • Relational aspects neglected in scientific impact assessment  Academic SNS as a new source for SNA in science • Case study of ResearchGate: low activity and density, high homophily and interesting centrality effects  Network position partly explanable by other measures of influence • Following structure overlaps significantly with co-authorship
  • 3. ASNA Zurich, August 29 2013 Page 3 Measuring Impact in Science 1
  • 4. ASNA Zurich, August 29 2013 Page 4 Academic Impact Is A Multi-Faceted Construct
  • 5. ASNA Zurich, August 29 2013 Page 5 Academic Impact: New vs. Old Bibliometrics from Peer-reviewed JournalsUsage-based Metrics
  • 6. ASNA Zurich, August 29 2013 Page 6 Usage-based metrics • Publication on the web enables new metrics:  Webometrics  Scientometrics 2.0/Altmetrics • Goal: achieving a more current and differentiated picture of impact • Using social media data for person-based and article-based metrics (Priem & Hemminger, 2010; Shema, Bar-Ilan & Thelwall, 2013; Thelwall et al., 2013)
  • 7. ASNA Zurich, August 29 2013 Page 7 Example: ImpactStory
  • 8. ASNA Zurich, August 29 2013 Page 8 What about Social Capital and Relations? • Relations with other researchers are important resources - Promotion - Publication - Invitation - Collaboration… • Social capital matters  Bringing in the relational aspect in impact measurement… beyond citations
  • 9. ASNA Zurich, August 29 2013 Page 9 The ResearchGate Project 2
  • 10. ASNA Zurich, August 29 2013 Page 10 What is ResearchGate? • Biggest SNS for scientists with 3 million users • Based in Berlin and founded in 2008 • More than 30 million publication entries • Vivid community, especially popular with young researchers in emerging countries
  • 11. ASNA Zurich, August 29 2013 Page 11
  • 12. ASNA Zurich, August 29 2013 Page 12 The Project • Evaluating new forms of impact in management research • Intensity of interaction, followers, followees, activity, publication resonance, RG score etc. • 55 participants from 11 institutes: 80 percent male • 50 percent PhD, 30 post-doc/assistant profs and 20 percent full profs
  • 13. ASNA Zurich, August 29 2013 Page 13 The Network • 55 nodes, 10 isolates • Av. Degree=3 • Density=0.06 • Diameter=6 • Av. Path Length=2.43 • E-I Index=-0.08 (expected: 0.69) • Clustering=0.48
  • 14. ASNA Zurich, August 29 2013 Page 14 Network and Institute Membership E-I Index: -0.08 (expected: 0.69) Clustering: 0.48 (0.27)
  • 15. ASNA Zurich, August 29 2013 Page 15 Prediciting Network Centrality Indegree Closeness Betweenness Eigenvector Seniority (Reference: Master student=0) PhD Student (1) Post-Doc without Professorship (2) Junior/Assistant Professor (3) Full Professor (4) .11** .28*** n. s. n. s. .46** .71*** n. s. n. s. .66*** .39** .89*** .83*** n. s. n. s. n. s. n. s. .22** n. s. .70*** n. s. Publication Success (WOS h-Index; off platform) .37* n. s. n. s. n. s. n. s. Publication Resonance (on platform) n. s. .43* n. s. n. s. .36* Online Activity .50*** .40** .21** n. s. .41*** ResearchGate Score n. s. n. s. n. s. n. s. R2 70% 50% 37% 41% 54%
  • 16. ASNA Zurich, August 29 2013 Page 16 Network and Academic Position Blue=PhD Black=Postdoc/Project Leader White=Assistant Professor Red=Full Professor
  • 17. ASNA Zurich, August 29 2013 Page 17 The Co-Authorship Network Coloring=Institute Size=Indegree
  • 18. ASNA Zurich, August 29 2013 Page 18 QAP-correlating Follower and Co-Authorship Network Do the networks overlap? Do researchers who write articles together also follow each other? Yes… but the correlation is not very strong: 0.09 (p-value: 0.025)
  • 19. ASNA Zurich, August 29 2013 Page 19 Summary • Indegree and closeness allrounders, betweenness most distinct • Activity most important predictor of centrality (reciprocity) • Academic position important but differentiated picture (inverted u-shape?) • Publication success (h-index) important for overall indegree but not for faculty-specific indegree • High homophily and clustering and low activity
  • 20. ASNA Zurich, August 29 2013 Page 20 The Road Ahead • Sample extension to other research areas and universities • More sophisticated data by including different social media • Combining centrality with other criteria • Looking at other publications (proceedings, book chapters…) • ERGMing the s*** out of the data
  • 21. ASNA Zurich, August 29 2013 Page 21 Thank You For Your Attention
  • 22. ASNA Zurich, August 29 2013 Page 22 Interested in the Project and Collaboration? Mail: christoph.lutz@unisg.ch ResearchGate: http://www.researchgate.net/profile/Christoph_Lutz/ Academia.edu: http://independent.academia.edu/ChristophLutz Mendeley: http://www.mendeley.com/profiles/christoph-lutz1/ @lutzid