SIGNLENS: A Tool for Analyzing People's Polarization Social Relationship Based on Signed Graph Modeling
Keywords:Human computer interaction; social media tools; navigation and visualization, Studies of digital humanities (culture, history, arts) using social media, Subjectivity in textual data; sentiment analysis; polarity/opinion identification and extraction, linguistic analyses of social media behavior
AbstractSIGNLENS 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.
How to Cite
Huang, J., Shen, H., & Cheng, X. (2021). SIGNLENS: A Tool for Analyzing People’s Polarization Social Relationship Based on Signed Graph Modeling. Proceedings of the International AAAI Conference on Web and Social Media, 15(1), 1091-1093. https://doi.org/10.1609/icwsm.v15i1.18136