A deep dive into location-based communities in social discovery networks

Kanchana Thilakarathna; Suranga Seneviratne; Kamal Gupta; Mohamed Ali Kaafar; Aruna Seneviratne

doi:10.1016/j.comcom.2016.11.008

A deep dive into location-based communities in social discovery networks

Kanchana Thilakarathna^*, Suranga Seneviratne, Kamal Gupta, Mohamed Ali Kaafar, Aruna Seneviratne

^*Corresponding author for this work

Research output: Contribution to journal › Article

9 Citations (Scopus)

Abstract

Location-based social discovery networks (LBSD) is an emerging category of location-based social networks (LBSN) that are specifically designed to enable users to discover and communicate with nearby people. In this paper, we present the first measurement study of the characteristics and evolution of location-based communities which are based on a social discovery network and geographic proximity. We measure and analyse more than 176K location-based communities with over 1.4 million distinct members of a popular social discovery network and more than 46 million locations. We characterise the evolution of the communities and study the user behaviour in LBSD by analysing the mobility features of users belonging to communities in comparison to non-community members. Using observed spatio-temporal similarity features, we build and evaluate a classifier to predict location-based community membership solely based on user mobility information.

Original language	English
Pages (from-to)	78-90
Number of pages	13
Journal	Computer Communications
Volume	100
DOIs	https://doi.org/10.1016/j.comcom.2016.11.008
Publication status	Published - 1 Mar 2017
Externally published	Yes

Keywords

human mobility
link prediction
social discovery networks

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10.1016/j.comcom.2016.11.008

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AU - Seneviratne, Aruna

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