Social media are becoming increasingly popular in scientific communication. A range of platforms, such as academic social networking sites ( SNS ), are geared specifically towards the academic community. Proponents of the altmetrics approach have pointed out that new media allow for new avenues of scientific impact assessment. Traditional impact measures based on bibliographic analysis have long been criticized for overlooking the relational dynamics of scientific impact. We therefore propose an application of social network analysis to researchers' interactions on an academic social networking site to generate potential new metrics of scientific impact. Based on a case study conducted among a sample of S wiss management scholars, we analyze how centrality measures derived from the participants' interactions on the academic SNS R esearch G ate relate to traditional, offline impact indicators. We find that platform engagement, seniority, and publication impact contribute to members' indegree and eigenvector centrality on the platform, but less so to closeness or betweenness centrality. We conclude that a relational approach based on social network analyses of academic SNS , while subject to platform‐specific dynamics, may add richness and differentiation to scientific impact assessment.
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Hoffmann et al. (2015) studied this question.
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