An overview of opinion polarization: models, drivers, and strategic solutions

• Presenting a multidisciplinary framework for understanding opinion polarization. • Classifying polarization models from individual behavior-influenced, group dynamics-driven, and network structure-shaped perspectives. • Investigating the psychological, social, and technological drivers of opinion polarization. • Proposing multi-level strategic solutions to address polarization. • Identifying challenges, and future directions in polarization research. In the context of social media and algorithmic personalization shaping information flows, opinion polarization poses a significant challenge to information processing and decision making. In this paper, we retrieved Web of Science records and applied a multi-stage screening process, yielding 145 rigorously selected papers on opinion polarization. From these sources, we developed a three-dimensional classification framework categorizing polarization models into individual behavior, group dynamics, and network structure. Our analysis reveals that cognitive bias in information processing, identity homophily within social groups, and algorithmic filtering in online platforms serve as core drivers of digital opinion polarization. Based on these insights, we propose strategic solutions across four interdependent domains: information level interventions, dialogue level facilitation, technology level adjustments, and psychology level guidance. We illustrate how these measures can be operationalized to mitigate echo chamber effects and foster cross-cutting engagement. This review synthesizes existing research to offer a structured foundation for understanding complex polarization mechanisms. It also provides a theoretical basis for future cross-platform dynamic modeling and policy development. Finally, we identify critical research gaps and outline future directions, highlighting the need for adaptive AI-driven moderation strategies, dynamic polarization models, and coordinated cross-platform policy interventions in the evolving digital landscape.

Institutions

Publication Details

Journal
Information Processing & Management
Published
2025-10-07
DOI
https://doi.org/10.1016/j.ipm.2025.104433
Primary Topic
Microbial Community Ecology and Physiology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An overview of opinion polarization: models, drivers, and strategic solutions

Information Processing & Management
Microbial Community Ecology and Physiology
article

An overview of opinion polarization: models, drivers, and strategic solutions

article en

Abstract

• Presenting a multidisciplinary framework for understanding opinion polarization. • Classifying polarization models from individual behavior-influenced, group dynamics-driven, and network structure-shaped perspectives. • Investigating the psychological, social, and technological drivers of opinion polarization. • Proposing multi-level strategic solutions to address polarization. • Identifying challenges, and future directions in polarization research. In the context of social media and algorithmic personalization shaping information flows, opinion polarization poses a significant challenge to information processing and decision making. In this paper, we retrieved Web of Science records and applied a multi-stage screening process, yielding 145 rigorously selected papers on opinion polarization. From these sources, we developed a three-dimensional classification framework categorizing polarization models into individual behavior, group dynamics, and network structure. Our analysis reveals that cognitive bias in information processing, identity homophily within social groups, and algorithmic filtering in online platforms serve as core drivers of digital opinion polarization. Based on these insights, we propose strategic solutions across four interdependent domains: information level interventions, dialogue level facilitation, technology level adjustments, and psychology level guidance. We illustrate how these measures can be operationalized to mitigate echo chamber effects and foster cross-cutting engagement. This review synthesizes existing research to offer a structured foundation for understanding complex polarization mechanisms. It also provides a theoretical basis for future cross-platform dynamic modeling and policy development. Finally, we identify critical research gaps and outline future directions, highlighting the need for adaptive AI-driven moderation strategies, dynamic polarization models, and coordinated cross-platform policy interventions in the evolving digital landscape.

Information Processing & ManagementVol. 63(2)
Universidad de Jaén (ES), Sichuan University (CN)
Openalex Percentile: Top 40%
Microbial Community Ecology and Physiology
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.

An overview of opinion polarization: models, drivers, and strategic solutions · Information Processing & Management (2025) | TGRS Research Map | TGRS