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Physical Sciences and Mathematics Commons

Open Access. Powered by Scholars. Published by Universities.®

Databases and Information Systems

Research Collection School Of Computing and Information Systems

2015

Social network services

Articles 1 - 2 of 2

Full-Text Articles in Physical Sciences and Mathematics

On Neighborhood Effects In Location-Based Social Networks, Thanh-Nam Doan, Freddy Chong-Tat Chua, Ee-Peng Lim Dec 2015

On Neighborhood Effects In Location-Based Social Networks, Thanh-Nam Doan, Freddy Chong-Tat Chua, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

In this paper, we analyze factors that determine the check-in decisions of users on venues using a location-based social network dataset. Based on a Foursquare dataset constructed from Singapore-based users, we devise a stringent criteria to identify the actual home locations of a subset of users. Using these users' check-ins, we aim to ascertain the neighborhood effect on the venues visited, compared with the activity level of users. We further formulate the check-in count prediction and check-in prediction tasks. A comprehensive set of features have been defined and they encompass information from users, venues, their neighbors, and friendship networks. We …


Joint Search By Social And Spatial Proximity, Kyriakos Mouratidis, Jing Li, Yu Tang, Nikos Mamoulis Mar 2015

Joint Search By Social And Spatial Proximity, Kyriakos Mouratidis, Jing Li, Yu Tang, Nikos Mamoulis

Research Collection School Of Computing and Information Systems

The diffusion of social networks introduces new challenges and opportunities for advanced services, especially so with their ongoing addition of location-based features. We show how applications like company and friend recommendation could significantly benefit from incorporating social and spatial proximity, and study a query type that captures these two-fold semantics. We develop highly scalable algorithms for its processing, and enhance them with elaborate optimizations. Finally, we use real social network data to empirically verify the efficiency and efficacy of our solutions.