EvoRiver: Visual Analysis of Topic Coopetition on Social Media

Abstract

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).

Interplay between Public Attention and Public Emotion toward Multiple Social Issues on Twitter

“…Twitter users use closely related words or adopt similar linguistic styles to express their interest in related issues (e.g., Economy, Employment, and Spending), which makes it easier to capture the cooperation, instead of competition, between social issues [38, 39]. The contrasting findings may also be attributed to the pairwise interaction that is examined in this study.…”

“…We only focused on the interaction between two social issues. However, it has been found that two related social issues can work jointly to attract public attention from the third issue [38]. In other words, higher-order and more complicated interaction between multiple social issues can exist among social issues to recruit public attention.…”

Topic Tomographies (TopTom): a visual approach to distill information from media streams

“…In most of the solutions the main visualization adopts a time‐based visual models, using the horizontal axis to represent time and the vertical one to represent volume of documents. Stacked graphs, area charts and stream graphs [BW08] are widely used to visually represent the change in volume of the same object [WLS∗10,LYK∗12] When dealing with topics aggregating over time alluvial diagrams [RB10], are used to provide an idea of flows tearing apart and reconnecting [CLT∗11,SWL∗14,LYW∗16].…”

Spatial–temporal visualization of city-wide crowd movement

“…Wu et al Wu et al (2014) also focused on the diffusion of opinions and developed a visual analytics system to measure opinion propagation among Twitter users and FluxFlow Zhao et al (2014) focused on the analysis of anomalous information spread. Sun et al Sun et al (2014) modeled the competition process among topics by measuring the influence of topic leaders and designed a time-based visualization, EvoRiver, to explore such interactions.…”