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SIGNLENS: A Tool for Analyzing People’s Polarization Social Relationship Based on Signed Graph Modeling

Authors

Junjie Huang,Huawei Shen,Xueqi Cheng

CAS Key Laboratory of Network Data Science and Technology, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China University of Chinese Academy of Sciences, Beijing, China,CAS Key Laboratory of Network Data Science and Technology, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China University of Chinese Academy of Sciences, Beijing, China,CAS Key Laboratory of Network Data Science and Technology, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China University of Chinese Academy of Sciences, Beijing, China


Proceedings:

Vol. 15 (2021): Fifteenth International AAAI Conference on Web and Social Media

Volume

Issue:

Vol. 15 (2021): Fifteenth International AAAI Conference on Web and Social Media

Track:

Demonstration Papers

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Abstract:

SIGNLENS is a tool that helps to analyze polarized social relationships based on signed graph modeling. It could be used by political analysts, historical researchers, and social media community organizations to analyze the social network with negative links (i.e., conflicts or disagreement). SIGNLENS can handle signed temporal graph by doing individual analysis and group analysis. Individual analysis gives a Web dashboard to users to explore the nodes who users focus on. Group analysis provides another perspective of analyzing the whole graph, which mainly analyzes the changes in the unbalance of the signed graph over time. We give two examples to demonstrate how our tool works, which consist of The China Biographical Database and the United States Congress Vote. More details about these two examples can be found in https://github.com/huangjunjie-cs/SIGNLENS.

DOI:

10.1609/icwsm.v15i1.18136


ICWSM

Vol. 15 (2021): Fifteenth International AAAI Conference on Web and Social Media