- Jianan Yao, Alexander Hauptmann. 2018. News Recommendation and Filter Bubble. Abstract: Recently many literatures have studied the problem of rumor detection on social media and proposed various automatic detection algorithms. In this ongoing work report we exploit the power of the crowd and formulate the reviewer selection problem, which aim to find reliable reviews for a possible rumor. Our reviewer selection scheme can be considered complementary to existing methods. We give theoretical analysis and provide a greedy algorithm with approximation guarantee. We conduct experiments on a Twitter dataset about rumors, which validates the effectiveness and efficiency of our algorithm.
