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• W2792906717 abstract "Abstract While ever more companies use Enterprise Social Networks for knowledge management, there is still a lack of understanding of users’ knowledge exchanging behavior. In this context, it is important to be able to identify and characterize users who contribute and communicate their knowledge in the network and help others to get their work done. In this paper, we propose a new methodological approach consisting of three steps, namely “message classification”, “identification of users’ roles” as well as “characterization of users’ roles”. We apply the approach to a dataset from a multinational consulting company, which allows us to identify three user roles based on their knowledge contribution in messages: givers, takers, and matchers. Going beyond this categorization, our data shows that whereas the majority of messages aims to share knowledge, matchers, that means people that give and take, are a central element of the network. In conclusion, the development and application of a new methodological approach allows us to contribute to a more refined understanding of users’ knowledge exchanging behavior in Enterprise Social Networks which can ultimately help companies to take measures to improve their knowledge management." @default.
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• W2792906717 date "2018-04-01" @default.
• W2792906717 modified "2023-09-24" @default.
• W2792906717 title "“Thanks for sharing”—Identifying users’ roles based on knowledge contribution in Enterprise Social Networks" @default.
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• W2792906717 doi "https://doi.org/10.1016/j.comnet.2018.02.012" @default.
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