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This paper addresses social network embedding, which aims to embed social network nodes, including user profile information, into a latent low-dimensional space. Most of the existing works on network embedding only consider network structure, but ignore user-generated content that could be potentially helpful in learning a better joint network representation. Different from rich node content in citation networks, user profile information in social networks is useful but noisy, sparse, anddoi:10.24963/ijcai.2017/472 dblp:conf/ijcai/ZhangYZZ17 fatcat:ztmxzsrpobf77ieem32hd2cmpa