A Survey of Signed Network Mining in Social Media

Author:

Tang Jiliang1,Chang Yi2,Aggarwal Charu3,Liu Huan4

Affiliation:

1. Michigan State University, East Lansing, MI

2. Yahoo Research, Sunnyvalue, CA

3. IBM T.J. Watson Research Center, Yorktown, NY

4. Arizona State University, Tempe, AZ

Abstract

Many real-world relations can be represented by signed networks with positive and negative links, as a result of which signed network analysis has attracted increasing attention from multiple disciplines. With the increasing prevalence of social media networks, signed network analysis has evolved from developing and measuring theories to mining tasks. In this article, we present a review of mining signed networks in the context of social media and discuss some promising research directions and new frontiers. We begin by giving basic concepts and unique properties and principles of signed networks. Then we classify and review tasks of signed network mining with representative algorithms. We also delineate some tasks that have not been extensively studied with formal definitions and also propose research directions to expand the field of signed network mining.

Funder

the U.S. Army Research Office

U.S. Army Research Office

the Office of Naval Research

the Army Research Laboratory

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

Reference163 articles.

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3. Charu C. Aggarwal. 2011. An Introduction to Social Network Data Analytics. Springer. Charu C. Aggarwal. 2011. An Introduction to Social Network Data Analytics. Springer.

4. Nir Ailon Yudong Chen and Xu Huan. 2013. Breaking the small cluster barrier of graph clustering. arXiv preprint arXiv:1302.4549 (2013). Nir Ailon Yudong Chen and Xu Huan. 2013. Breaking the small cluster barrier of graph clustering. arXiv preprint arXiv:1302.4549 (2013).

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