Abstract
Enterprise social software tools are increasingly being used to support the communication and collaboration between employees, as well as to facilitate the collaborative organisation of information and knowledge within companies. Not only do these tools help to develop and maintain an efficient social organisation, they also produce massive amounts of fine-grained data on collaborations, communication and other forms of social relationships within an enterprise. In this chapter, we argue that the availability of these data provides unique opportunities to monitor and analyse social structures and their impact on the success and performance of individuals, teams, communities and organisations. We further review methods from the planning, design and optimisation of telecommunication networks and discuss challenges arising when wanting to apply them to optimise the structure of enterprise social networks.
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Notes
- 1.
The Laplacian matrix L of an undirected network is commonly defined as \(\mathbf{L} = \mathbf{D} -\mathbf{A}\), where A is the usual binary adjacency matrix of the network and D is a diagonal matrix where diagonal elements contain the degree sequence of the network.
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Burger, V., Hock, D., Scholtes, I., Hoßfeld, T., Garcia, D., Seufert, M. (2014). Social Network Analysis in the Enterprise: Challenges and Opportunities. In: Zweig, K., Neuser, W., Pipek, V., Rohde, M., Scholtes, I. (eds) Socioinformatics - The Social Impact of Interactions between Humans and IT. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-319-09378-9_7
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