EvoRiver: Visual Analysis of Topic Coopetition on Social Media

• Published in: IEEE transactions on visualization and computer graphics Vol. 20; no. 12; pp. 1753 - 1762
• Main Authors: Sun, Guodao, Wu, Yingcai, Liu, Shixia, Peng, Tai-Quan, Zhu, Jonathan J. H., Liang, Ronghua
• Format: Journal Article
• Language: English
• Published: United States IEEE 31.12.2014; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Computer Graphics; Cooperation; Data visualization; Humans; Informatics - methods; Information Dissemination; Media; Models, Theoretical; Social Media; Social network services; Social networks; Visual analytics; Topic coopetition; information diffusion; time-based visualization; information propagation
• ISSN: 1077-2626; 1941-0506
• DOI: 10.1109/TVCG.2014.2346919

Cooperation and competition (jointly called "coopetition") are two modes of interactions among a set of concurrent topics on social media. How do topics cooperate or compete with each other to gain public attention? Which topics tend to cooperate or compete with one another? Who plays the key role in coopetition-related interactions? We answer these intricate questions by proposing a visual analytics system that facilitates the in-depth analysis of topic coopetition on social media. We model the complex interactions among topics as a combination of carry-over, coopetition recruitment, and coopetition distraction effects. This model provides a close functional approximation of the coopetition process by depicting how different groups of influential users (i.e., "topic leaders") affect coopetition. We also design EvoRiver, a time-based visualization, that allows users to explore coopetition-related interactions and to detect dynamically evolving patterns, as well as their major causes. We test our model and demonstrate the usefulness of our system based on two Twitter data sets (social topics data and business topics data).