SSNE:Status Signed Network Embedding

摘要：

　　This work studies the problem of signed network embedding,which aims to obtain low-dimensional vectors for nodes in signed networks.Existing works mostly focus on learning representations via characterizing the social structural balance theory in signed networks.However,structural balance theory could not well satisfy some of the fundamental phenomena in real-world signed networks such as the direction of links.As a result,in this paper we integrate another theory Status Theory into signed network embedding since status theory can better explain the social mechanisms of signed networks.To be specific,we characterize the status of nodes in the semantic vector space and well design different ranking objectives for positive and negative links respectively.Besides,we utilize graph attention to assemble the information of neighborhoods.We conduct extensive experiments on three real-world datasets and the results show that our model can achieve a significant improvement compared with baselines.

关键词： Signed network embedding Attention Status theory

作者: Chunyu Lu Pengfei Jiao Hongtao Liu Yaping Wang Hongyan Xu Wenjun Wang

作者单位: College of Intelligence and Computing,Tianjin University,Tianjin,China Center for Biosafety Research and Strategy,Tianjin University,Tianjin,China

会议类型: 国际会议

会议名称: The 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (第23届亚太知识发现和数据挖掘国际会议(PAKDD2019)

会议地点: 澳门

会议语种:英文

页码: 81-93

在线出版日期: 2019-04-14（万方平台首次上网日期，不代表论文的发表时间）