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dc.contributor.authorRiemer, Kai
dc.contributor.authorLee, Laurence Lock
dc.contributor.authorKjaer, Cai
dc.contributor.authorHaeffner, Annika
dc.date.accessioned2018-08-24
dc.date.available2018-08-24
dc.date.issued2018-08-24
dc.identifier.issn1738-1744
dc.identifier.urihttp://hdl.handle.net/2123/18696
dc.descriptionThis research was funded by a Business School Industry Partnership grant, in collaboration with SWOOP Analytics Pty Ltd.en_AU
dc.description.abstractWe report on research, carried out in collaboration with SWOOP Analytics, to identify metrics that allow distinguishing groups in Enterprise Social Networks (ESN) according to their activity patterns. The emerging field of ESN Analytics has made inroads into providing metrics and models to measure 1) the health and structural properties of enterprise social networks, as well as 2) the activity pattern and distinct behavioural roles of individual users. What is lacking so far is ESN Analytics at the group level. Yet, groups play an important role in ESNs for organising communication and collabo-ration activity. In this study we carry out explorative research employing cluster analysis to identify metrics that best distinguish a sample of 350 ESN groups from three organisations into distinct types. We identify three metrics as most useful: 1) the Gini coefficient, measuring (un)evenness of user par-ticipation, 2) density, measuring the extent to which users interact with each other, and 3) reciprocity, measuring the response rate to messages within the group. The resulting typology of four groups, broadcast streams, information forums, communities of practice and project teams, will be useful for network managers and group leaders to check how well their group is tracking against intended group activity pattern.en_AU
dc.description.sponsorshipSWOOP Analytics Pty Ltden_AU
dc.language.isoen_AUen_AU
dc.relation.ispartofseriesBIS WP2018-01en_AU
dc.subjectEnterprise Social Networken_AU
dc.subjectESN Analyticsen_AU
dc.subjectAnalyticsen_AU
dc.subjectESNen_AU
dc.subjectGroupsen_AU
dc.subjectTypologyen_AU
dc.subjectCluster Analysisen_AU
dc.titleWhat’s in a Group? Identification of group types for Enterprise Social Network Analytics using SWOOP dataen_AU
dc.typeWorking Paperen_AU
dc.contributor.departmentBusiness and Information Systemsen_AU


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