2022/03/07 by Ran Wang, Kehan Du, Qianhe Chen +6 · 7 citations
Computer Science · Physics and Astronomy · Social Sciences · #Artificial intelligence #Complex Network Analysis Techniques #Computer science #Data Visualization and Analytics #Data science #Data visualization #Glyph (data visualization) #Human–computer interaction #Misinformation and Its Impacts #Rumor #Social media #Task (project management) #Visual analytics #Visualization #World Wide Web #cs.HC
paper · pdf · doi:10.1145/3491101.3519712
published in CHI Conference on Human Factors in Computing Systems Extended Abstracts, 1-7
arxiv created 2022/03/07 · arxiv updated 2022/03/08 · openalex publication_date 2022/04/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
With the development of social media, various rumors can be easily spread on the Internet and such rumors can have serious negative effects on society. Thus, it has become a critical task for social media platforms to deal with suspected rumors. However, due to the lack of effective tools, it is often difficult for platform administrators to analyze and validate rumors from a large volume of information on a social media platform efficiently. We have worked closely with social media platform administrators for four months to summarize their requirements of identifying and analyzing rumors, and further proposed an interactive visual analytics system, RumorLens, to help them deal with the rumor efficiently and gain an in-depth understanding of the patterns of rumor spreading. RumorLens integrates natural language processing (NLP) and other data processing techniques with visualization techniques to facilitate interactive analysis and validation of suspected rumors. We propose well-coordinated visualizations to provide users with three levels of details of suspected rumors: an overview displays both spatial distribution and temporal evolution of suspected rumors; a projection view leverages a metaphor-based glyph to represent each suspected rumor and further enable users to gain a quick understanding of their overall characteristics and similarity with each other; a propagation view visualizes the dynamic spreading details of a suspected rumor with a novel circular visualization design, and facilitates interactive analysis and validation of rumors in a compact manner. By using a real-world dataset collected from Sina Weibo, one case study with a domain expert is conducted to evaluate