A Novel Approach for Predicting the Outcome of Request in RAOP Dataset
In today’s era, online social communities such as Q&A sites are widely used for asking favors, so it would be beneficial to formulate a technique that would help in predicting the success of the response. The objective of the paper is to enhance the accuracy of prediction of the success of altruistic request that follows the same approach as used by ADJ (Proceedings of AAAI International Conference on Web and Social Media, ICWSM, 2014 . Three more features are proposed, i.e., topic, role, and centrality in addition to the features proposed by ADJ ) to capture user’s interaction in the past and topic effect on the prediction of response. We also propose a graph-based success prediction (GSP) model that uses feature weights and uses the underlying graph structure for the propagation to predict the outcome of a request. Experiments were conducted on the RAOP dataset which belongs to sub-community of Reddit.com using GSP, and it outperformed ADJ and other baseline methods using limited training data.
KeywordsSuccess prediction Altruistic request Social interactions
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