Modeling the spread of false news on social networking sites

• Main Author: Concepcion, Aleena Marie R.
• Format: text
• Language: English
• Published: Animo Repository 2021
• Subjects: Fake news; Disinformation; Industrial Engineering; Operations Research, Systems Engineering and Industrial Engineering
• Online Access: https://animorepository.dlsu.edu.ph/etdb_induseng/3; https://animorepository.dlsu.edu.ph/context/etdb_induseng/article/1001/viewcontent/Final_Thesis_Concepcion_T2_AY_2020_21_Modeling_the_spread_of_false_news_on_social_networking_sites.pdf
• Institution: De La Salle University

The problem of false news online has continued to worsen, especially after significant events around the world from the 2018 Cambridge Analytica scandal, COVID-19 pandemic, to the recent January 6th Insurrection at the US Capitol. False information online has distorted online users’ perception of the real world. As daily life is more intertwined with the digital world, false news becomes more a more urgent concern because of the way it can shape public opinion. With that, a rumor propagation model, which was based on epidemiological models was adopted to model the spread of false news on social networking sites. The existing model was expanded on the STELLA software to consider the cognitive process of users when encountering false news, the platform in which the false news spreads, the relationship of false news with online users, and vice versa. After having modeled the spread of false news, it was found that Confirmation Bias and Sharing of posts were the two critical loops of the model. Scenario and Solution analysis were done to further examine which interventions to consider for the final policy design. It was found that possible interventions include reducing the bias of users at a wide-scale level, taxing SNS to fund news organizations, or restructuring the SNS algorithm.