Audience Analysis for Competing Memes in Social Media


  • Samuel Carton University of Michigan
  • Souneil Park Telefonica Research
  • Nicole Zeffer University of Michigan
  • Eytan Adar University of Michigan
  • Qiaozhu Mei University of Michigan
  • Paul Resnick University of Michigan



information diffusion, visualization, sankey diagram, twitter, rumor, audience analysis


Existing tools for exploratory analysis of information diffusion in social media focus on the message senders who actively diffuse the meme. We develop a tool for audience analysis, focusing on the people who are passively exposed to the messages, with a special emphasis on competing memes such as propagations and corrections of a rumor. In such competing meme diffusions, important questions include which meme reached a bigger total audience, the overlap in audiences of the two, and whether exposure to one meme inhibited propagation of the other. We track audience members’ states of interaction, such as having been exposed to one meme or another or both. We analyze the marginal impact of each message in terms of the number of people who transition between states as a result of that message. These marginal impacts can be computed efficiently, even for diffusions involving thousands of senders and millions of receivers. The marginal impacts provide the raw material for an interactive tool, RumorLens, that includes a Sankey diagram and a network diagram. We validate the utility of the tool through a case study of nine rumor diffusions. We validate the usability of the tool through a user study, showing that nonexperts are able to use it to answer audience analysis questions.




How to Cite

Carton, S., Park, S., Zeffer, N., Adar, E., Mei, Q., & Resnick, P. (2021). Audience Analysis for Competing Memes in Social Media. Proceedings of the International AAAI Conference on Web and Social Media, 9(1), 41-50.