Mathematical Modeling of Individual Behavior Based on Viewpoint Dynamics: Analyzing Group Cohesion Effects Induced by Individual Potential Power Differences

The group cohesion effect refers to individuals’ identification with the group’s viewpoint, resulting from behavioral and cognitive changes during interactions, and is crucial for group development. However, individual differences in intrinsic characteristics lead to varied group behaviors and cohesion. This paper uses a mathematical model based on viewpoint dynamics to explore how these differences shape group cohesion. The primary consideration is the potential power inherent in individual characteristics, which can be understood as symmetry-breaking concepts. In the model, individuals are classified into two types, each supporting one of two viewpoints. The potential power reflects the individuals’ degree of firmness regarding their viewpoint and their perceptual range. Differences in the potential power, both within and between types, drive shifts in viewpoints and behaviors, generating diverse cohesion effects. Additionally, the model also incorporates the influence of group size and external factors, such as individuals with no viewpoints and those holding public opinion viewpoints. The results indicate that group size has no significant effect on group cohesion, while individuals with no viewpoints contribute to stabilizing it, whereas individuals with public opinions weaken it. These findings highlight the complex relationship between individual differences in potential power and group cohesion, suggesting that symmetry-breaking dynamics can effectively explain group cohesion effects.

Authors

Institutions

Publication Details

Journal
Symmetry
Published
2025-02-12
DOI
https://doi.org/10.3390/sym17020282
Primary Topic
Opinion Dynamics and Social Influence
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mathematical Modeling of Individual Behavior Based on Viewpoint Dynamics: Analyzing Group Cohesion Effects Induced by Individual Potential Power Differences

Xuebo Chen, Chenyang Li, Yonghui Yang
Symmetry
Opinion Dynamics and Social Influence
article

Mathematical Modeling of Individual Behavior Based on Viewpoint Dynamics: Analyzing Group Cohesion Effects Induced by Individual Potential Power Differences

Xuebo Chen, Chenyang Li, Yonghui Yang
article en

Abstract

The group cohesion effect refers to individuals’ identification with the group’s viewpoint, resulting from behavioral and cognitive changes during interactions, and is crucial for group development. However, individual differences in intrinsic characteristics lead to varied group behaviors and cohesion. This paper uses a mathematical model based on viewpoint dynamics to explore how these differences shape group cohesion. The primary consideration is the potential power inherent in individual characteristics, which can be understood as symmetry-breaking concepts. In the model, individuals are classified into two types, each supporting one of two viewpoints. The potential power reflects the individuals’ degree of firmness regarding their viewpoint and their perceptual range. Differences in the potential power, both within and between types, drive shifts in viewpoints and behaviors, generating diverse cohesion effects. Additionally, the model also incorporates the influence of group size and external factors, such as individuals with no viewpoints and those holding public opinion viewpoints. The results indicate that group size has no significant effect on group cohesion, while individuals with no viewpoints contribute to stabilizing it, whereas individuals with public opinions weaken it. These findings highlight the complex relationship between individual differences in potential power and group cohesion, suggesting that symmetry-breaking dynamics can effectively explain group cohesion effects.

SymmetryVol. 17(2)
University of Science and Technology Liaoning (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 98%
Opinion Dynamics and Social Influence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.