Abstract
The rise of online social networks has created novel opportunities to analyze people by their hidden “honest” traits. In this paper we suggest automatic grouping of employees into virtual tribes based on their language and values. Tribes are groups of people homogenous within themselves and heterogenous to other groups. In this project we identify members of digital virtual tribes by the words they use in their everyday language, characterizing email users by applying four macro-categories based on their belief systems (alternative realities, personality, recreation, and ideology) developed in earlier research. Each macro-category is divided into four orthogonal categories, for instance “Alternative Realities” includes the categories “Fatherlanders”, “Treehuggers”, “Nerds”, and “Spiritualists”. We use the Tribefinder tool to analyze two email archives, the individual mailbox of an active academic and corporate consultant, and the Enron email archive. We found tribes for each user and analyzed the communication habits of each tribe, showing that members of different tribes significantly differ in how they communicate by email. This demonstrates the applicability of our approach to distinguish members of different virtual tribes by either language used or email communication structure and dynamics.
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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee with the Helsinki declaration and its later amendments or comparable with ethical standards.
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Morgan, L., Gloor, P.A. (2020). Identifying Virtual Tribes by Their Language in Enterprise Email Archives. In: Przegalinska, A., Grippa, F., Gloor, P. (eds) Digital Transformation of Collaboration. COINs 2019. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-030-48993-9_8
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