Cross-Site Virtual Social Network Construction

Chenhao Xie; Deqing Yang; Jingrui He; Yanghua Xiao

doi:10.1109/ICDMW.2015.98

Cross-Site Virtual Social Network Construction

Chenhao Xie, Deqing Yang, Jingrui He, Yanghua Xiao

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Given the plethora of social networking sites, it can be difficult for users to browse too many sites and discover social friends. For example, for a new diabetes patient, how can s/he find the users with similar symptoms on different dedicated sites and form supporting groups with them? Since different sites may use different vocabularies, this problem is challenging to match users across different sites. To address it, in this paper, we present a tool to demonstrate how to construct a virtual social network across multiple social networking sites. Specifically, it uses bipartite graphs to represent the relation ships between users and their posts' keywords in each site, it bridges the gap between different vocabularies of different sites based on their semantic relatedness through concept-based interpretations, and it uses an efficient propagation algorithm to obtain the similarity between users from different sites, which can be used to construct the cross-site virtual social network.

Original language	English (US)
Title of host publication	Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015
Editors	Xindong Wu, Alexander Tuzhilin, Hui Xiong, Jennifer G. Dy, Charu Aggarwal, Zhi-Hua Zhou, Peng Cui
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1660-1663
Number of pages	4
ISBN (Electronic)	9781467384926
DOIs	https://doi.org/10.1109/ICDMW.2015.98
State	Published - Jan 29 2016
Externally published	Yes
Event	15th IEEE International Conference on Data Mining Workshop, ICDMW 2015 - Atlantic City, United States Duration: Nov 14 2015 → Nov 17 2015

Publication series

Name	Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015

Other

Other	15th IEEE International Conference on Data Mining Workshop, ICDMW 2015
Country/Territory	United States
City	Atlantic City
Period	11/14/15 → 11/17/15

Keywords

Graph propagation
cross-site
semantic matching
virtual social network

ASJC Scopus subject areas

Electrical and Electronic Engineering
Computer Science Applications

Online availability

10.1109/ICDMW.2015.98

Library availability

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Cite this

Xie, C., Yang, D., He, J., & Xiao, Y. (2016). Cross-Site Virtual Social Network Construction. In X. Wu, A. Tuzhilin, H. Xiong, J. G. Dy, C. Aggarwal, Z-H. Zhou, & P. Cui (Eds.), Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015 (pp. 1660-1663). Article 7395882 (Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICDMW.2015.98

Cross-Site Virtual Social Network Construction. / Xie, Chenhao; Yang, Deqing; He, Jingrui et al.
Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015. ed. / Xindong Wu; Alexander Tuzhilin; Hui Xiong; Jennifer G. Dy; Charu Aggarwal; Zhi-Hua Zhou; Peng Cui. Institute of Electrical and Electronics Engineers Inc., 2016. p. 1660-1663 7395882 (Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Xie, C, Yang, D, He, J & Xiao, Y 2016, Cross-Site Virtual Social Network Construction. in X Wu, A Tuzhilin, H Xiong, JG Dy, C Aggarwal, Z-H Zhou & P Cui (eds), Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015., 7395882, Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015, Institute of Electrical and Electronics Engineers Inc., pp. 1660-1663, 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015, Atlantic City, United States, 11/14/15. https://doi.org/10.1109/ICDMW.2015.98

Xie C, Yang D, He J, Xiao Y. Cross-Site Virtual Social Network Construction. In Wu X, Tuzhilin A, Xiong H, Dy JG, Aggarwal C, Zhou Z-H, Cui P, editors, Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015. Institute of Electrical and Electronics Engineers Inc. 2016. p. 1660-1663. 7395882. (Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015). doi: 10.1109/ICDMW.2015.98

Xie, Chenhao ; Yang, Deqing ; He, Jingrui et al. / Cross-Site Virtual Social Network Construction. Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015. editor / Xindong Wu ; Alexander Tuzhilin ; Hui Xiong ; Jennifer G. Dy ; Charu Aggarwal ; Zhi-Hua Zhou ; Peng Cui. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 1660-1663 (Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015).

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abstract = "Given the plethora of social networking sites, it can be difficult for users to browse too many sites and discover social friends. For example, for a new diabetes patient, how can s/he find the users with similar symptoms on different dedicated sites and form supporting groups with them? Since different sites may use different vocabularies, this problem is challenging to match users across different sites. To address it, in this paper, we present a tool to demonstrate how to construct a virtual social network across multiple social networking sites. Specifically, it uses bipartite graphs to represent the relation ships between users and their posts' keywords in each site, it bridges the gap between different vocabularies of different sites based on their semantic relatedness through concept-based interpretations, and it uses an efficient propagation algorithm to obtain the similarity between users from different sites, which can be used to construct the cross-site virtual social network.",

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N2 - Given the plethora of social networking sites, it can be difficult for users to browse too many sites and discover social friends. For example, for a new diabetes patient, how can s/he find the users with similar symptoms on different dedicated sites and form supporting groups with them? Since different sites may use different vocabularies, this problem is challenging to match users across different sites. To address it, in this paper, we present a tool to demonstrate how to construct a virtual social network across multiple social networking sites. Specifically, it uses bipartite graphs to represent the relation ships between users and their posts' keywords in each site, it bridges the gap between different vocabularies of different sites based on their semantic relatedness through concept-based interpretations, and it uses an efficient propagation algorithm to obtain the similarity between users from different sites, which can be used to construct the cross-site virtual social network.

AB - Given the plethora of social networking sites, it can be difficult for users to browse too many sites and discover social friends. For example, for a new diabetes patient, how can s/he find the users with similar symptoms on different dedicated sites and form supporting groups with them? Since different sites may use different vocabularies, this problem is challenging to match users across different sites. To address it, in this paper, we present a tool to demonstrate how to construct a virtual social network across multiple social networking sites. Specifically, it uses bipartite graphs to represent the relation ships between users and their posts' keywords in each site, it bridges the gap between different vocabularies of different sites based on their semantic relatedness through concept-based interpretations, and it uses an efficient propagation algorithm to obtain the similarity between users from different sites, which can be used to construct the cross-site virtual social network.

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Cross-Site Virtual Social Network Construction

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