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Opinion dynamics with backfire effect and biased assimilation.

Xi Chen¹, Panayiotis Tsaparas², Jefrey Lijffijt¹

¹Department of Electronics and Information Systems, IDLab, Ghent University, Ghent, Belgium.

|September 1, 2021

Summary

This summary is machine-generated.

In today's media landscape, distinguishing fact from fiction is difficult. This study introduces a new opinion dynamics model incorporating biased assimilation and the backfire effect to explain opinion evolution and polarization in social networks.

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Area of Science:

Social Sciences
Computational Social Science
Network Science

Background:

The proliferation of AI content generation and mass media access blurs the lines between fact and fiction.
Understanding opinion evolution in networked environments lacking objective reality is a significant challenge.
Existing models often simplify social influence, neglecting key psychological phenomena.

Purpose of the Study:

To propose a novel opinion formation model integrating Biased Assimilation and the Backfire Effect.
To analyze opinion dynamics within social networks under these combined psychological influences.
To identify conditions leading to opinion polarization and consensus.

Main Methods:

Development of a new DeGroot-type opinion formation model.
Incorporation of Biased Assimilation: adopting similar opinions.
Inclusion of the Backfire Effect: entrenchment in opposing views.
Theoretical and empirical analysis of the model's behavior.

Main Results:

The model captures the Backfire Effect in opinion dynamics, a novel contribution.
Identified intuitive conditions governing the emergence of polarization.
Revealed conditions conducive to reaching consensus within the network.
Characterized the properties of opinions resulting from the model's dynamics.

Conclusions:

The proposed model offers a more realistic framework for opinion formation in complex social networks.
Biased Assimilation and the Backfire Effect significantly influence opinion polarization and consensus.
The findings provide insights into how individuals' opinions evolve amidst misinformation and social influence.