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Who will follow whom?:Exploiting semantics for link prediction in attention-information networks

Rowe, Matthew and Stankovic, Milan and Alani, Harith (2012) Who will follow whom?:Exploiting semantics for link prediction in attention-information networks. In: International Semantic Web Conference 2012, 2012-11-112012-11-15.

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Abstract

Existing approaches for link prediction, in the domain of network science, exploit a network's topology to predict future connections by assessing existing edges and connections, and inducing links given the presence of mutual nodes. Despite the rise in popularity of Attention-Information Networks (i.e. microblogging platforms) and the production of content within such platforms, no existing work has attempted to exploit the semantics of published content when predicting network links. In this paper we present an approach that fills this gap by a) predicting follower edges within a directed social network by exploiting concept graphs and thereby significantly outperforming a random baseline and models that rely solely on network topology information, and b) assessing the different behaviour that users exhibit when making follower-addition decisions. This latter contribution exposes latent factors within social networks and the existence of a clear need for topical affinity between users for a follow link to be created.

Item Type: Conference or Workshop Item (Paper)
Journal or Publication Title: International Semantic Web Conference 2012
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: Faculty of Science and Technology > School of Computing & Communications
ID Code: 58275
Deposited By: ep_importer_pure
Deposited On: 24 Sep 2012 15:56
Refereed?: Yes
Published?: Published
Last Modified: 17 Sep 2013 10:08
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/58275

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