Leveraging Friendship Networks for Dynamic Link Prediction in Social Interaction Networks

Authors

  • Ruthwik Junuthula University of Toledo
  • Kevin Xu University of Toledo
  • Vijay Devabhaktuni University of Toledo

DOI:

https://doi.org/10.1609/icwsm.v12i1.15059

Keywords:

link prediction, interaction network, friendship network

Abstract

On-line social networks (OSNs) often contain many different types of relationships between users. When studying the structure of OSNs such as Facebook, two of the most commonly studied networks are friendship and interaction networks. The link prediction problem in friendship networks has been heavily studied. There has also been prior work on link prediction in interaction networks,independent of friendship networks. In this paper, we study the predictive power of combining friendship and interaction networks. We hypothesize that, by leveraging friendship networks, we can improve the accuracy of link prediction in interaction networks. We augment several interaction link prediction algorithms to incorporate friendships and predicted friendships. From experiments on Facebook data, we find that incorporating friendships into interaction link prediction algorithms results in higher accuracy, but incorporating predicted friendships does not when compared to incorporating current friendships.

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Published

2018-06-15

How to Cite

Junuthula, R., Xu, K., & Devabhaktuni, V. (2018). Leveraging Friendship Networks for Dynamic Link Prediction in Social Interaction Networks. Proceedings of the International AAAI Conference on Web and Social Media, 12(1). https://doi.org/10.1609/icwsm.v12i1.15059