Modeling Polarization Caused by Empathetic and Repulsive Reaction in Online Social Network

Hirakura, Naoki; Aida, Masaki; Kawashima, Konosuke

doi:10.1587/transcom.2021ebp3150

Cited by 4 publications

(5 citation statements)

References 26 publications

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“…In [102], the authors concluded that providing subtle accuracy nudges is a promising approach to improving the quality of shared news. The correlation between SNSB and polarization was analyzed and verified [119]. Arguably, there is also a correlation between SNSB and individual PSOC constructs.…”

Section: Polarization Dimension As Shown In Tablementioning

confidence: 87%

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

Altoe,

Moreira,

Pinto

et al. 2024

Human Behavior and Emerging Technologies

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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.

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Section: Polarization Dimension As Shown In Tablementioning

confidence: 87%

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

Altoe,

Moreira,

Pinto

et al. 2024

Human Behavior and Emerging Technologies

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show abstract

“…We extend the interaction rules of our previously proposed one-dimensional opinion formation model [18] to multiple dimensions. We briefly describe the characteristics of the interaction rules of this one-dimensional model.…”

Section: Interaction Rulesmentioning

confidence: 99%

“…Another distance ∆ ′ j = 2a − ∆ j can be defined by considering periodic boundary conditions. The significant characteristic of this model is that the same framework describes the reaction of empathy and repulsion by using the distance of vectors with periodic boundary conditions [18]. Given that smaller differences in opinion make it easier to establish empathy and that larger differences in opinion make repulsion more likely, the probabilities of empathy p e,j and repulsion p r,j in dimension j are defined as follows:…”

Section: Interaction Rulesmentioning

confidence: 99%

On relationships between similarity of topics and opinion formation

Hirakura,

Aida

2024

NOLTA

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The spread of social media has caused the problem of opinion polarization as an unexpected side effect. Therefore, it is important to elucidate the mechanism of opinion formation through communications on social media. In this paper, we clarify the relationship between the degree of similarity among topics and opinion formation in multi-dimensional opinion formation that deals with multiple topics. For this objective, we use the multi-dimensional opinion formation model that we have proposed in the past. This model has the advantage of being able to avoid the "curse of dimensionality" and of being able to handle relationships among topics. We focus on how much the formation of an opinion on a particular topic influences the opinion held on other topics. Numerical experiments show that the higher the similarity between topics, the stronger the influence.

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“…We extend the interaction rules of our previously proposed one-dimensional opinion formation model [5] to multiple dimensions. In this one-dimensional model, periodic boundary conditions are imposed at both ends of the interval where opinion values can be taken, and two types of reactions, empathy and repulsion, are defined by the same form exponential functions.…”

Section: Interaction Rulesmentioning

confidence: 99%

“…Another distance ∆ ′ j = 2a − ∆ j can be defined by considering periodic boundary conditions. The significant characteristic of this model is that the reaction of empathy and repulsion are described by the same framework by using the distance of vectors with periodic boundary conditions [5]. Given that smaller differences in opinion make it easier to establish empathy and that larger differences in opinion make repulsion more likely, the probabilities of empathy p e, j and repulsion p r, j in dimension j are defined as follows:…”

Section: Interaction Rulesmentioning

confidence: 99%

A multi-dimensional opinion formation model for online social networks

Hirakura

Aida

2022

IEICE ComEX

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In this paper, we propose a multi-dimensional opinion formation model for online social networks. Previous studies have not taken into account the "curse of dimensionality" that comes from the higher-dimensional state space used in multi-dimensional opinion formation; the dimensionality is high as opinions with various types of preferences must be handled simultaneously. Conventionally, the interactions between users are limited to static models in which the topics that users discuss are predetermined and do not change. Our proposed method can avoid the above problems with previous studies by introducing low-dimensional subspaces for interacting user pairs by using word distributed representation. We propose a dynamic model that allows users to discuss various topics at each interaction. Simulations of the proposed model show that discussion focused on a particular topic encourages opinion formation.

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Modeling Polarization Caused by Empathetic and Repulsive Reaction in Online Social Network

Cited by 4 publications

References 26 publications

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

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

On relationships between similarity of topics and opinion formation

A multi-dimensional opinion formation model for online social networks

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