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2015
Springer

Distance and Friendship: A Distance-Based Model for Link Prediction in Social Networks

3 years 5 months ago
Distance and Friendship: A Distance-Based Model for Link Prediction in Social Networks
With the emerging of location-based social networks, study on the relationship between human mobility and social relationships becomes quantitatively achievable. Understanding it correctly could result in appealing applications, such as targeted advertising and friends recommendation. In this paper, we focus on mining users’ relationship based on their mobility information. More specifically, we propose to use distance between two users to predict whether they are friends. We first demonstrate that distance is a useful metric to separate friends and strangers. By considering location popularity together with distance, the difference between friends and strangers gets even larger. Next, we show that distance can be used to perform an effective link prediction. In addition, we discover that certain periods of the day are more social than others. In the end, we use a machine learning classifier to further improve the prediction performance. Extensive experiments on a Twitter dataset ...
Yang Zhang, Jun Pang
Added 16 Apr 2016
Updated 16 Apr 2016
Type Journal
Year 2015
Where APWEB
Authors Yang Zhang, Jun Pang
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