One-sided Versus Two-sided: A Novel Opinion Dynamics Information-Type Education-Based Hegselmann–Krause Model

Xu, Minghua; Luo, Ziling; Liu, Ruixin; Wang, Bang; Han, Xu

doi:10.1109/smc52423.2021.9658647

Cited by 2 publications

(1 citation statement)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is an important finding as it suggests that polarization can be avoided if education on fake news posts happens at the initial stages of a social network before its consequent evolution to consensus. It was demonstrated in [81] that it is more difficult for someone to reach a consensus with a person who belongs to a group with a higher proportion of loweducated people than with a higher proportion of higheducated people. Another data point that shows the importance of educating online users on fake news posts.…”

Section: Opinion Dynamics Dimensionmentioning

confidence: 99%

Online Fake News Opinion Spread and Belief Change: A Systematic Review

Altoe,

Moreira,

Pinto

et al. 2024

Human Behavior and Emerging Technologies

View full text Add to dashboard Cite

Fake news has been linked to the rise of psychological disorders, the increased disbelief in science, and the erosion of democracy and freedom of speech. Online social networks are arguably the main vehicle of fake news spread. Educating online users with explanations is one way of preventing this spread. Understanding how online belief is formed and changed may offer a roadmap for such education. The literature includes surveys addressing online opinion formation and polarization; however, they usually address a single domain, such as politics, online marketing, health, and education, and do not make online belief change their primary focus. Unlike other studies, this work is the first to present a cross-domain systematic literature review of user studies, methodologies, and opinion model dimensions. It also includes the orthogonal polarization dimension, focusing on online belief change. We include peer-reviewed works published in 2020 and later found in four relevant scientific databases, excluding theoretical publications that did not offer validation through dataset experimentation or simulation. Bibliometric networks were constructed for better visualization, leading to the organization of the papers that passed the review criteria into a comprehensive taxonomy. Our findings show that a person’s individuality is the most significant influential force in online belief change. We show that online arguments that balance facts with emotionally evoking content are more efficient in changing their beliefs. Polarization was shown to be cross-correlated among multiple subjects, with politics being the central polarization pole. Polarized online networks start as networks with high opinion segregation, evolve into subnetworks of consensus, and achieve polarization around social network influencers. Trust in the information source was demonstrated to be the chief psychological construct that drives online users to polarization. This shows that changing the beliefs of influencers may create a positive snowball effect in changing the beliefs of polarized online social network users. These findings lay the groundwork for further research on using personalized explanations to reduce the harmful effects of online fake news on social networks.

show abstract

Section: Opinion Dynamics Dimensionmentioning

confidence: 99%