Bridging the gap between physical location and online social networks

Justin Cranshaw · Eran Toch · Jason Hong · Aniket Kittur · Norman Sadeh

441 citations0/0 files storedACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp)

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Human Mobility and Location-Based Analysis Complex Network Analysis Techniques Privacy-Preserving Technologies in Data

Abstract

This paper examines the location traces of 489 users of a location sharing social network for relationships between the users' mobility patterns and structural properties of their underlying social network. We introduce a novel set of location-based features for analyzing the social context of a geographic region, including location entropy, which measures the diversity of unique visitors of a location. Using these features, we provide a model for predicting friendship between two users by analyzing their location trails. Our model achieves significant gains over simpler models based only on direct properties of the co-location histories, such as the number of co-locations. We also show a positive relationship between the entropy of the locations the user visits and the number of social ties that user has in the network. We discuss how the offline mobility of users can have implications for both researchers and designers of online social networks.

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References

1973The Strength of Weak Ties 2007The Benefits of Facebook “Friends:” Social Capital and College Students’ Use of Online Social Network Sites 2008Understanding individual human mobility patterns 1998Internet paradox: A social technology that reduces social involvement and psychological well-being?2009Inferring friendship network structure by using mobile phone data 2008Understanding mobility based on GPS data 2009Eigenbehaviors: identifying structure in routine 2009Eigenbehaviors: identifying structure in routine

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2014Measuring Large-Scale Social Networks with High Resolution 2013Accidental, open and everywhere: Emerging data sources for the understanding of cities 2011Location-Based Social Networks: Users 2018Analyzing large-scale human mobility data: a survey of machine learning methods and applications 2010Empirical models of privacy in location sharing 2017A Neural Network Approach to Jointly Modeling Social Networks and Mobile Trajectories

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