Visual Thinking Algorithms for Visualization of Social Media Memes, Topics, and Communities

Visual Thinking Algorithms (VTA’s) are a tool for designing interactive visualizations by describing the operation of a human-computer cognitive system, accounting for strengths and limitations of the human visual system and cognitive processing. In this paper, we apply this methodology to visualization of memes and related topics and communities (groups of users with common topics) arising in social media messages. Based on a cognitive task analysis we define a MemeVis concept design for exploratory social media analysis embodying VTA’s such as brushing, drilldown, lateral exploration, and generalized fisheye view. We then describe two early prototype displays: a Meme Pool featuring a network graph for exploring meme-topiccommunity relationships, and a Community Network Explorer enabling exploration of cross-community similarity with drilldown to users and user posts within a community. We close with recommendations for future research including design of a VTA-based toolkit and expanded views for social media analysis and monitoring.