Enabling Knowledge Broker Analysis through Actor Clusters in Organizational Structures in Enterprise Social Media
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Journal Title
Journal ISSN
Volume Title
A4 Artikkeli konferenssijulkaisussa
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Author
Date
2022
Major/Subject
Mcode
Degree programme
Language
en
Pages
9
585-593
585-593
Series
Proceedings of the 55th Hawaii International Conference on System Sciences 2022, Proceedings of the Annual Hawaii International Conference on System Sciences
Abstract
Knowledge brokers serve as facilitators of knowledge sharing. The extant literature calls for nuanced analyses of different organizational structures as the spaces knowledge brokers operate in. Our interest lies in formal, semiformal, and informal organizational network structures and in how knowledge brokers are positioned in them. In this paper, we outline a collaborative analysis method, with researchers from different disciplines working together in data sprints. The benefit of this process is that it enables analyzing large organizational networks with deep insights. Amplifying social network analysis with field knowledge offers a deeper understanding of the connections in the network. This paper describes the analysis process and proposes interdisciplinary data processing techniques. We applied the proposed method using an extensive empirical data set that includes intraorganizational social media interactions between employees in a global organization. Our analysis transforms enterprise social media data into a network model that describes an organization’s social structure.Description
Keywords
cluster detection, data-sprint, knowledge broker, social network analysis
Other note
Citation
Leppälä, M & Huhtamäki, J 2022, Enabling Knowledge Broker Analysis through Actor Clusters in Organizational Structures in Enterprise Social Media . in Proceedings of the 55th Hawaii International Conference on System Sciences 2022 . Proceedings of the Annual Hawaii International Conference on System Sciences, Hawaii International Conference on System Sciences, pp. 585-593, Annual Hawaii International Conference on System Sciences, Manoa, Hawaii, United States, 04/01/2022 . https://doi.org/10.24251/HICSS.2022.071