{"type":"ScholarlyArticle","title":"BANANA: when Behavior ANAlysis meets social Network Alignment","authors":[{"name":"Fuxin Ren","slug":"fuxin-ren","given":"Fuxin","family":"Ren","affiliation":"State Key Laboratory of Networking and Switching Technology , Beijing University of Posts and Telecommunications , Beijing , China"},{"name":"Zhongbao Zhang","slug":"zhongbao-zhang","given":"Zhongbao","family":"Zhang","affiliation":"State Key Laboratory of Networking and Switching Technology , Beijing University of Posts and Telecommunications , Beijing , China"},{"name":"Jiawei Zhang","slug":"jiawei-zhang","given":"Jiawei","family":"Zhang","affiliation":"IFM Lab , Department of Computer Science , Florida State University , FL , USA"},{"name":"Sen Su","slug":"sen-su","given":"Sen","family":"Su","affiliation":"State Key Laboratory of Networking and Switching Technology , Beijing University of Posts and Telecommunications , Beijing , China"},{"name":"Li Sun","slug":"li-sun","given":"Li","family":"Sun","affiliation":"State Key Laboratory of Networking and Switching Technology , Beijing University of Posts and Telecommunications , Beijing , China"},{"name":"Guozhen Zhu","slug":"guozhen-zhu","given":"Guozhen","family":"Zhu","affiliation":"State Key Laboratory of Networking and Switching Technology , Beijing University of Posts and Telecommunications , Beijing , China"},{"name":"Congying Guo","slug":"congying-guo","given":"Congying","family":"Guo","affiliation":"State Key Laboratory of Networking and Switching Technology , Beijing University of Posts and Telecommunications , Beijing , China"}],"abstract":"Recently, aligning users among different social networks has received significant attention. However, most of the existing studies do not consider users’ behavior information during the aligning procedure and thus still suffer from the poor learning performance. In fact, we observe that social network alignment and behavior analysis can benefit from each other. Motivated by such an observation, we propose to jointly study the social network alignment problem and user behavior analysis problem. We design a novel end-to-end framework named BANANA. In this framework, to leverage behavior analysis for social network alignment at the distribution level, we design an earth mover’s distance based alignment model to fuse users’ behavior information for more comprehensive user representations. To further leverage social network alignment for behavior analysis, in turn, we design a temporal graph neural network model to fuse behavior information in different social networks based on the alignment result. Two models above can work together in an end-to-end manner. Through extensive experiments on real-world datasets, we demonstrate that our proposed approach outperforms the state-of-the-art methods in the social network alignment task and the user behavior analysis task, respectively.","doi":"10.24963/ijcai.2020/200","url":"https://ijcai.org/proceedings/2020/200","pdf":"https://ijcai.org/proceedings/2020/0200.pdf","markdown":"https://ijcai.org/proceedings/2020/200.md","bibtex":"https://ijcai.org/proceedings/2020/bibtex/200","volume":{"slug":"2020","title":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2020","url":"https://ijcai.org/proceedings/2020/","year":2020,"location":"Yokohama","dates":"January 2021 (postponed from 11-17 July 2020)","editors":"Christian Bessiere","isbn":"978-0-9992411-6-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2020"},"section":"Data Mining","track":"Main track","number":200,"pages":{"first":1438,"last":1444},"keywords":["Humans and AI: Personalization and User Modeling","Data Mining: Applications","Data Mining: Mining Text, Web, Social Media"],"videos":[{"label":"Video","url":"https://videos.ijcai20.org/24166/file_24166.m3u8","length_sec":282,"provider":"hls"}],"references":[{"position":1,"raw":"[Baytas et al., 2017] Inci M Baytas, Cao Xiao, Xi Zhang, Fei Wang, Anil K Jain, and Jiayu Zhou. 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