Echo Chamber and Polarization in Social Media: An Agent-Based Modeling Approach

Description

This book addresses increasingly relevant social problems enabled by social media through the lens of system science research and modeling. Instead of evaluating existing patterns from existing social media data, the book focuses on exploring the possibility of various policies. Specifically, it provides fresh insight into the political echo chamber and polarization in social media using agent-based modeling and scenario analysis.  The book contains a practical framework to study the factors influencing echo chambers and polarization formation occurring in social media communication. By modeling individual social media users' information consumption, the influence of various behaviors and policies are captured as macro-phenomena. The book also introduces a comprehensive agent-based reinterpretation of the Zaller model, a classic in public opinion research. In addition, the book demonstrates two real-life applications of the model using empirical observations: resolving the conflicting observations of the online echo chamber effect, and modeling the influence of vaccine-related Facebook pages on users’ opinions about vaccination. Contents About the Author List of Figures List of Tables 1 Introduction 1.1 The Echo Chamber and Polarization Problem in Social Media 1.2 Contribution Summary 1.3 Book Organization 2 Conceptual Backgrounds 2.1 Echo Chamber and Polarization 2.2 Communication and Public Opinion in Social Media 2.3 Modeling Opinion Formation 2.4 Zaller Model of Public Opinion 2.5 Argument Against the Anti-vaccination Movements 3 Methodology 3.1 Agent-Based Modeling for Social Simulation 3.2 Policy Design Using Landscape Search 4 Simulating Echo Chamber and Polarization Problems in Social Media 4.1 Background 4.2 Model Summary 4.3 Measuring Echo Chamber and Polarization in SNS 4.4 Simulation Scenario and Parameters 4.4.1 Simulation Stages 4.4.2 Scenario Description 4.5 Results and Discussion 4.5.1 Role of News in Echo Chamber and Polarization Formation 4.5.2 Echo Chamber Analysis Individual Echo Chamber Coefficient Evaluation Global Echo Chamber Evaluation Average Opinion Evaluation Average Exposure Evaluation Overall Discussion 4.5.3 Model Validation 4.6 Reversing Polarization 4.6.1 Model, Measurements, and Simulation Public Opinion and Polarization Measurement 4.6.2 Simulation 4.6.3 Results and Discussion 5 Agent-Based Interpretation of the Zaller Model 5.1 Background 5.2 Agent-Based Interpretation of the Zaller Model 6 Application 1: Resolving the Conflicting Observation of Online Echo Chambers 6.1 Motivation 6.2 Model Overview 6.2.1 News and Media 6.2.2 User Agents and SNS 6.2.3 Agents' Dynamics 6.3 Simulation 6.4 Results and Discussion 6.4.1 Landscape Analysis 6.4.2 Model Validation 7 Application 2: Simulating the Influence of Facebook Pages on Individual Attitudes Toward Vaccination 7.1 Motivation 7.2 Model Overview 7.2.1 Basic Percolation Model 7.2.2 Baseline Model 7.3 Simulation 7.3.1 Simulation Overview and Settings 7.3.2 Simulating Policies 7.3.3 Parameter Measurement 7.4 Results and Discussion 7.4.1 Basic Percolation Results 7.4.2 Baseline Model Results 7.4.3 Scenario Analysis 7.4.4 Model Validation 8 Conclusions and Future Works 8.1 Conclusions 8.2 Future Works 8.3 Afterword A Additional Information A.1 Formal Definition of Modeling Echo Chamber and Polarization in Social Media A.1.1 News A.1.2 User Agent A.1.3 User's State Transition Model A.2 Formal Definition of Agent-Based Interpretation of the Zaller Model A.2.1 Model Entities and Assumptions A.2.2 Media Agent A.2.3 User Agents A.2.4 Process of News Consumption A.2.5 Survey Process Bibliography