Title :
Discovering and Profiling Overlapping Communities in Location-Based Social Networks
Author :
Zhu Wang ; Daqing Zhang ; Xingshe Zhou ; Dingqi Yang ; Zhiyong Yu ; Zhiwen Yu
Author_Institution :
Sch. of Comput. Sci., Northwestern Polytech. Univ., Xi´an, China
Abstract :
With the recent surge of location-based social networks (LBSNs), such as Foursquare and Facebook Places, huge digital footprints of people´s locations, profiles, and online social connections become accessible to service providers. Unlike social networks (e.g., Flickr, Facebook) that have explicit groups for users to subscribe to or join, LBSNs usually have no explicit community structure. In order to capitalize on the large number of potential users, quality community detection and profiling approaches are needed. In the meantime, the diversity of people´s interests and behaviors when using LBSNs suggests that their community structures overlap. In this paper, based on the user check-in traces at venues and user/venue attributes, we come out with a novel multimode multi-attribute edge-centric coclustering framework to discover the overlapping and hierarchical communities of LBSNs users. By employing both intermode and intramode features, the proposed framework is not only able to group like-minded users from different social perspectives but also discover communities with explicit profiles indicating the interests of community members. The efficacy of our approach is validated by intensive empirical evaluations using the collected Foursquare dataset.
Keywords :
mobile computing; pattern clustering; social networking (online); Facebook places; Foursquare; LBSN; community detection; community members; digital footprints; like-minded users; location-based social networks; multimode multiattribute edge-centric coclustering framework; overlapping community discovery; overlapping community profiling; service providers; user check-in traces; user-venue attributes; Community profiling; hierarchical clustering; location-based social networks (LBSNs); overlapping community detection;
Journal_Title :
Systems, Man, and Cybernetics: Systems, IEEE Transactions on
DOI :
10.1109/TSMC.2013.2256890