|Author||Tang, Jiliang ♦ Chang, Yi ♦ Aggarwal, Charu ♦ Liu, Huan|
|Source||ACM Digital Library|
|Publisher||Association for Computing Machinery (ACM)|
|Subject Domain (in DDC)||Computer science, information & general works ♦ Data processing & computer science|
|Subject Keyword||Negative links ♦ Signed network mining ♦ Signed networks ♦ Social media|
|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.|
|Description||Author Affiliation: Michigan State University, East Lansing, MI (Tang, Jiliang); IBM T.J. Watson Research Center, Yorktown, NY (Aggarwal, Charu); Arizona State University, Tempe, AZ (Liu, Huan); Yahoo Research, Sunnyvalue, CA (Chang, Yi)|
|Age Range||18 to 22 years ♦ above 22 year|
|Education Level||UG and PG|
|Learning Resource Type||Article|
|Publisher Place||New York|
|Journal||ACM Computing Surveys (CSUR)|
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