To simulate rumor propagation on Twitter during the COVID-19 pandemic, a new rumor propagation model, called SIP (Spreader-Ignorant-Philosopher), was built based on the traditional SIR disease spreading model. The rumor spreading behavior and the social media mechanism are theorized through Gabriel Tarde’s Law of Imitation and Bruno Latour’s Actor- Network Theory (ANT). Considering rumor as invention, the spreading behavior as imitation, and humans and features of social media as actors in a network, an agent-based approach was used to implement the SIP model. Corresponding to the ANT, non-human features are incorporated in the model: 1. rumors and truth are initially spread by bots not humans; 2. humans communicate through tweets not direct messages; 3. tweets are posted and viewed in hashtags not individual feeds. An intervention method, inserting truth bots, was tested for the effectiveness of deterring the rumors. The results show that truth bots can effectively remove rumors from a population of 1093 humans, no matter when and how many truth bots are inserted. The model provides a useful tool to explain rumor propagation as well as experiment with different policies during emergencies such as the COVID-19 pandemic.
Computer Science; Sociology and Anthropology
Guo, Zhen, "Defeating the COVID-19 Infodemic on Twitter: A SIP Agent-Based Model of Rumor Propagation and Truth Bot Intervention" (2021). Senior Independent Study Theses. Paper 9514.
Computer Engineering | Digital Communications and Networking | Politics and Social Change | Social Media | Sociology
COVID-19, Infodemic, agent-based modeling, Twitter, law of imitation, actor-network theory
Bachelor of Arts
Senior Independent Study Thesis
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