Conference Proceedings

Detecting location-centric communities using social-spatial links with temporal constraints

KH Lim, J Chan, C Leckie, S Karunasekera, A Hanbury (ed.), G Kazai (ed.), A Rauber (ed.), N Fuhr (ed.)

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Springer International Publishing | Published : 2015

Abstract

Community detection on social networks typically aims to cluster users into different communities based on their social links. The increasing popularity of Location-based Social Networks offers the opportunity to augment these social links with spatial information, for detecting location-centric communities that frequently visit similar places. Such location-centric communities are important to companies for their location-based and mobile advertising efforts. We propose an approach to detect location-centric communities by augmenting social links with both spatial and temporal information, and demonstrate its effectiveness using two Foursquare datasets. In addition, we study the effects of ..

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