Defeating the COVID-19 Infodemic on Twitter: A SIP Agent-Based Model of Rumor Propagation and Truth Bot Intervention
Student Name: Zhen Guo
Majors: Computer Science, Sociology
Advisors: Thomas Tierney (Sociology), Heather Guanera (Computer Science)
As stated by a World Health Organization (WHO) director, “We’re not just fighting an epidemic [COVID-19]; we’re fighting an infodemic” (Zarocostas 2020). Researchers and policy makers have tried different methods to stop rumor propagation to defeat the infodemic. To help them, I built a virtual Twitter world, where computer-generated agents view hashtags and write tweets just like humans, to test effective policies. My virtual Twitter experiment gives a real-world implication that removal of the initial rumor spreaders on social media might not be necessary, since all the human agents end up believing in truth when rumor bots are still active. This study explores the intersection of fields including sociology, communication, network science, and computer science. Gabriel Tarde’s Law of Imitation and Bruno Latour’s Actor-Network Theory served as the theoretical frameworks of my project. I utilized agent-based model and SIR model to develop a new model called Spreader-Ignorant-Philosopher (SIP) model. It suggests a new way of understanding a complex social phenomenon using simplified computer agents. In the future, a more refined and realistic model might be used to test the effectiveness of real-world policies prior to its application in the real population.
Zhen will be online to field comments on April 16: 2-4 pm EDT (PST 11am-1pm, Africa/Europe: evening). Zhen will be available for a chat on Teams during Real-time chat session. Join a chat through this link.
Posted in I.S. Symposium 2021 on March 25, 2021.
Related Areas of Study
Closely affiliated with the Anthropology program, sociology majors at The College of Wooster take core courses in research methods and theory.Major Minor
Solve complex problems with creative solutions using computer programming and applicationsMajor Minor