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    Inferring offline hierarchical ties from online social networks

    Jaber, Mohammad and Wood, Peter T. and Papapetrou, Panagiotis and Helmer, Sven (2014) Inferring offline hierarchical ties from online social networks. In: UNSPECIFIED (ed.) Proceedings of the companion publication of the 23rd international conference on World wide web companion. Geneva, Switzerland: International World Wide Web Conferences Steering Committee, pp. 1261-1266. ISBN 9781450327459.

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    Abstract

    Social networks can represent many different types of relationships between actors, some explicit and some implicit. For example, email communications between users may be represented explicitly in a network, while managerial relationships may not. In this paper we focus on analyzing explicit interactions among actors in order to detect hierarchical social relationships that may be implicit. We start by employing three well-known ranking-based methods, PageRank, Degree Centrality, and Rooted-PageRank (RPR) to infer such implicit relationships from interactions between actors. Then we propose two novel approaches which take into account the time-dimension of interactions in the process of detecting hierarchical ties. We experiment on two datasets, the Enron email dataset to infer manager-subordinate relationships from email exchanges, and a scientific publication co-authorship dataset to detect PhD advisor-advisee relationships from paper co-authorships. Our experiments show that time-based methods perform considerably better than ranking-based methods. In the Enron dataset, they detect 48% of manager-subordinate ties versus 32% found by Rooted-PageRank. Similarly, in co-author dataset, they detect 62% of advisor-advisee ties compared to only 39% by Rooted-PageRank.

    Metadata

    Item Type: Book Section
    School: Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
    Research Centres and Institutes: Birkbeck Knowledge Lab
    Depositing User: Peter Wood
    Date Deposited: 02 Jun 2014 09:50
    Last Modified: 09 Aug 2023 12:35
    URI: https://eprints.bbk.ac.uk/id/eprint/9834

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