Drowning Out Rumor: Dynamical Models of the Interaction between Spreaders of and Exposed to Truth and Rumor Spreading

Juan Miguel Augusto M. Feria1,3§,, Michael Lawrence S. Oliva,
Briane Paul V. Samson2,3,4, and Angelyn R. Lao1,3*

1Mathematics and Statistics Department, De La Salle University, Manila, Metro Manila 1004 Philippines
2Software Technology Department, De La Salle University, Manila, Metro Manila 1004 Philippines
3Center for Complexity and Emerging Technologies, De La Salle University,
Manila, Metro Manila 1004 Philippines
4Graduate School of Systems Information Science, Future University Hakodate,
Hakodate, Hokkaido 0418655 Japan

*Corresponding Author: This email address is being protected from spambots. You need JavaScript enabled to view it.
§Both authors contributed equally to this work





Social networking sites have become instrumental in spreading information online, which unfortunately includes rumors and misinformation. Past studies have investigated the spread of rumors without considering that truth may spread simultaneously. This study considers both the spread of truth and rumor and investigates the result of their coexistence in a population. We formulated the spreader-spreader interaction model and the exposed-spreader interaction model based on the epidemiological SEIR model. In the spreader-spreader interaction model, the spreaders try to influence the opposing spreaders whereas, in the exposed-spreader interaction model, the spreaders try to influence the exposed individuals from the opposing side. In our study, we calculated the reproduction numbers for truth and rumor, determined the stability of the model at the equilibrium points, and determined an approach for spreading truth while halting rumors. In the spreader-spreader model, we have shown that increasing the removal rate of Spreaders of Rumor decreases the prevalence of rumor in the population. Whereas in the exposed-spreader model, we showed that increasing the conversion rate of Exposed to Rumor to Exposed to Truth significantly increases the amount of Exposed to Truth in the population, thereby making it an effective mechanism for promoting the spread of truth. In conclusion, it is harder to control the information epidemic in the exposed-spreader model but, compared to the spreader-spreader model, information spreads faster according to the exposed-spreader model. For certain information to be endemic to a population, our study proposes that spreaders take advantage during the first few days of the information diffusion process.




Social networking sites are online platforms that connect us with our real-life friends in the digital realm. As technology progressed, entities like brands, news outlets, and people have utilized and transformed these social networking sites as platforms to spread influences, promote products, and increase audiences (Kandhway and Kuri 2014, Rodrigues 2016). While this phenomenon has benefited both influence-seekers for increased reach and the masses for serendipitous encounters of new information, this has also brought about negative externalities to our societies. One of which is the deliberate spread and amplification of misinformation and rumors, enabled by previously unknown accounts that are emerging and claiming ascendancy over established information sources (Del Vicario et al. 2016). Considering their evident societal impact, it is vital for us to understand how information spreads within these platforms and how to control it. . . . read more




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