Dimensions of User Behavior in Enterprise Social Networks

  • Janine HackerEmail author
  • Rebecca Bernsmann
  • Kai Riemer
Part of the Knowledge Management and Organizational Learning book series (IAKM, volume 3)


The analysis of user behavior in online communities is a prominent topic in social media research. As such, user behavior is often analyzed using a set of metrics that describe the user’s participation behavior and structural position in the social network. Yet, for Enterprise Social Networks (ESN), i.e. internally used social networking platforms, such research is lacking. While prior studies have found users to engage in knowledge-intensive interactions, e.g. discussing and developing new ideas, little is known about how to conceptualize and measure ESN user behavior. Being able to measure user behavior, however, is an important prerequisite for the identification of knowledge management-related roles in the context of ESN.

Against this backdrop, in this chapter we derive 30 metrics that characterize the participation behavior, message content and structural position of ESN users of an Australian professional services firm. Based on a factor analysis, we identify nine distinct dimensions of ESN user behavior: Social dispersion, engagement, focus, information sharing, discussing, information seeking, response time, receiving information, and tagging. With this research we contribute to the literature by transferring concepts and methods of organization science and social media research to an ESN context. Further, our approach forms the basis for the identification of different types of knowledge actors, which might ultimately help to improve organizational knowledge transparency.


Social Network Analysis User Behavior Betweenness Centrality Behavioral Dimension Organizational Knowledge 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Institute of Information SystemsFriedrich-Alexander-Universität Erlangen-NürnbergErlangenGermany
  2. 2.The University of Sydney Business SchoolUniversity of SydneySydneyAustralia

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