Social and place-focused communities in location-based online social networks

TL;DR

This study analyzes the structural differences between social and place-focused communities in location-based social networks, revealing distinct properties and the importance of place data for user-centric applications.

Contribution

It constructs and compares social and place-focused graphs, showing their structural differences and the limited overlap of communities, highlighting the significance of place data.

Findings

Social and place-focused graphs have different global and meso-scale structures.

Communities in social and place-focused graphs have negligible overlap.

Place-based group information is more useful for user applications than social communities.

Abstract

Thanks to widely available, cheap Internet access and the ubiquity of smartphones, millions of people around the world now use online location-based social networking services. Understanding the structural properties of these systems and their dependence upon users' habits and mobility has many potential applications, including resource recommendation and link prediction. Here, we construct and characterise social and place-focused graphs by using longitudinal information about declared social relationships and about users' visits to physical places collected from a popular online location-based social service. We show that although the social and place-focused graphs are constructed from the same data set, they have quite different structural properties. We find that the social and location-focused graphs have different global and meso-scale structure, and in particular that social and place-focused communities have negligible overlap. Consequently, group inference based on community detection performed on the social graph alone fails to isolate place-focused groups, even though these do exist in the network. By studying the evolution of tie structure within communities, we show that the time period over which location data are aggregated has a substantial impact on the stability of place-focused communities, and that information about place-based groups may be more useful for user-centric applications than that obtained from the analysis of social communities alone.