Identification of Enterprise Social Network (ESN) Group Archetypes in ESN Analytics

Metrics Selection and Case Application


  • Kai Riemer The University of Sydney
  • Laurence Lock Lee SWOOP Analytics Pty Ltd
  • Cai Kjaer SWOOP Analytics Ptd Ltd
  • Annika Haeffner Ulm University



Enterprise Social Network, ESN groups, ESN Analytics, Social Media Analytics


With the proliferation of Enterprise Social Networks (ESN), the measurement of ESN activity becomes increasingly relevant. The emerging field of ESN analytics aims to develop metrics and models to measure and classify user activity to support organisational goals and outcomes. In this paper we focus on a neglected area of ESN analytics, the classification of activity in ESN groups. We engage in explorative research to identify a set of metrics that divides an ESN group sample into distinct types. We collaborate with Sydney-based service provider SWOOP Analytics who provided access to actual ESN meta data describing activity in 350 groups across three organisations. By employing clustering techniques, we derive a set of four group types: broadcast streams, information forums, communities of practice and project teams. We collect and reflect on feedback from ESN champions in fourteen organisations. For ESN analytics research we contribute a set of metrics and group types. For practice we envision a method that enables group managers to compare aspirations for their groups to embody a certain group type, with actual activity patterns.




How to Cite

Riemer, K., Lee, L. L., Kjaer, C., & Haeffner, A. (2020). Identification of Enterprise Social Network (ESN) Group Archetypes in ESN Analytics: Metrics Selection and Case Application. Australasian Journal of Information Systems, 24.



Selected Papers from the Australasian Conference on Information Systems (ACIS)