User-based network embedding for opinion spammer detection

Ziyang Wang, Wei Wei, Xian-Ling Mao, Guibing Guo, Pan Zhou, Sheng Jiang

Abstract: Highlights•This paper jointly learning direct relevance and indirect relevance for collective spammers detection.•The direct relevance is captured by the pairwise behavior features between two users.•The indirect relevance is learned based on a k-step co-rating neighborhood proximity in the network.•Extensive experiments conducted on two real-world datasets verify the effectiveness of the proposed method.