Identification of User Roles in Enterprise Social Networks: Method Development and Application

Janine Hacker () and Kai Riemer ()
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Janine Hacker: University of Liechtenstein
Kai Riemer: The University of Sydney

Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, 2021, vol. 63, issue 4, No 4, 367-387

Abstract: Abstract The importance of gaining insights into informal organizational structures for management purposes is acknowledged by both research and practice. However, “traditional” approaches to analyzing informal organizational social networks involve significant manual effort and do not scale for larger datasets. Enterprise Social Networks (ESN) have emerged as important tools for informal employee interactions, such as for problem-solving and information sharing. While the analysis of ESN back end data might provide insights into the informal fabric of organizations, and in particular employees’ roles in such networks, there is a lack of systematic approaches for carrying out ESN analytics, such as for user role identification. Following a design science research process, a process-based method to identify user roles from ESN data was developed and evaluated. The method’s efficacy is demonstrated through an in-depth application in a case study of Australian professional services firm Deloitte. In doing so the paper shows how ESN data can be utilized to derive metrics that characterize participation behavior, message content, and structural network positions of ESN users.

Keywords: Social software; User roles; CRISP-DM; Role analysis; Knowledge management; Design science research methodology (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s12599-020-00648-x

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