How Fast Will You Get a Response? Predicting Interval Time for Reciprocal Link Creation

Authors

  • Vachik Dave Indiana University-Purdue University Indianapolis
  • Mohammad Al Hasan Indiana University-Purdue University Indianapolis
  • Chandan Reddy Virginia Polytechnic Institute and State University

Abstract

In the recent years, reciprocal link prediction has received some attention from the data mining and social network analysis researchers, who solved this problem as a binary classification task. However, it is also important to predict the interval time for the creation of reciprocal link. This is a challenging problem for two reasons: First, the lack of effective features, because well-known link prediction features are designed for undirected networks and for the binary classification task, hence they do not work well for the interval time prediction; Second, the presence of censored data instances makes the traditional supervised regression methods unsuitable for solving this problem. In this paper, we propose a solution for the reciprocal link interval time prediction task. We map this problem into survival analysis framework and show through extensive experiments on real-world datasets that, survival analysis methods perform better than traditional regression, neural network based model and support vector regression (SVR).

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Published

2017-05-03

How to Cite

Dave, V., Al Hasan, M., & Reddy, C. (2017). How Fast Will You Get a Response? Predicting Interval Time for Reciprocal Link Creation. Proceedings of the International AAAI Conference on Web and Social Media, 11(1), 508-511. Retrieved from https://ojs.aaai.org/index.php/ICWSM/article/view/14961