Dave, Vachik S.Al Hasan, MohammadReddy, Chandan K.2018-08-292018-08-292017Dave, V. S., & Al, M. (2017). How Fast Will You Get a Response? Predicting Interval Time for Reciprocal Link Creation. Proceedings of the Eleventh International Conference on Web and Social Media (ICWSM). Retrieved from https://par.nsf.gov/biblio/10048632-how-fast-you-get-response-predicting-interval-time-reciprocal-link-creationhttps://hdl.handle.net/1805/17213In 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).enPublisher Policyreciprocal altruisminterval timereciprocal linkArticle