Beyond Citation Counts : The Potential of Academic Social Network Sites for Scientific Impact Assessment
Type
presentation
Date Issued
2013-08-29
Author(s)
Abstract (De)
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.
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.
Language
German
Keywords
Social Network Sites
Social Media
Scientific Communication
Impact Assessment
Centrality
Social Network Analysis
HSG Classification
contribution to scientific community
HSG Profile Area
SoM - Business Innovation
Refereed
No
Event Title
10th International Conference on Applications of Social Network Analysis ASNA 2013
Event Location
Zürich
Subject(s)
Division(s)
Eprints ID
225360
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open.access
Name
asna christoph lutz.pdf
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Name
asna christoph lutz.pdf
Size
3.05 MB
Format
Adobe PDF
Checksum (MD5)
2dd2f6d136ffb3507d9507efe8804cc9