Epidemiological Modeling of Health Information Dynamics on Twitter

• Main Authors: Feeroz, Yusoph, Bernadas, Jan Michael Alexandre C., Cheng, Charibeth K., Lao, Angelyn
• Format: text
• Published: Animo Repository 2024
• Subjects: health communication; epidemiological modeling; SEIR; Twitter; reproduction number
• Online Access: https://animorepository.dlsu.edu.ph/apssr/vol24/iss1/8; https://animorepository.dlsu.edu.ph/context/apssr/article/1527/viewcontent/RA_207.pdf
• Institution: De La Salle University

Social media, like Twitter, has become a critical component in promoting public health. Due to the similar nature of information and viruses spreading, there is a new trend of using epidemiological models to study how information spreads on social media. In this study, the SEIR model is adapted to model how health information is disseminated over Twitter. Two models are presented: a basic Twitter interaction model and a model wherein the sentiments of tweets are considered. To our knowledge, these models are the first of their kind to study health information dynamics on Twitter and to understand the behavior of users based on the sentiments of tweets. In the basic interaction model (TwitHComm), we compared the dynamics of health information spreading of @WHO and @DOHgovph and found that the tweet data obtained from @DOHgovph do not achieve an epidemic state where @WHO does. In the model where sentiments were considered (TwitHCommS), despite increasing the number of positive sentiment tweets in the simulation, negative sentiments still influenced Twitter users. Overall, these models provide valuable information for using social media for public health communication.