Modeling the dynamics of misinformation spread on social media platforms - Arisman, Arisman; Simbolon, Hasanal Fachri Satia (Institute of Computer Science (IOCS), 2024)
This study employs the SEIRS (Susceptible-Exposed-Infectious-Recovered-Susceptible) model to investigate the dissemination dynamics of misinformation within a community. Utilizing a population of 100,000 individuals and a time frame of 500 units, the model incorporates parameters such as transmission rate, recovery rate from the exposed and infectious stages, and the rate of returning to susceptibility. Simulation results demonstrate the fluctuating patterns of individuals across stages, depicting an initial surge in exposure followed by a gradual decline as individuals transition into recovery or awareness of misinformation. This research underscores the SEIRS model's utility in comprehending misinformation spread and highlights the potential for behavioral shifts and societal awareness in mitigating its effects. Furthermore, it emphasizes the importance of interdisciplinary approaches, blending epidemiological, psychological, and sociological perspectives, to devise effective interventions combating misinformation dissemination. Ultimately, fostering digital and critical literacy alongside sustained educational efforts emerges as a crucial strategy in fostering healthier, more trustworthy information environments.