A mathematical model to reduce the polarization of opinions

In his research, Frank Valencia, a member of the Inria COMETE team at École Polytechnique's LIX, uses mathematics to apply formal methods to economic and social science models to analyze, and potentially modify, online belief formation, consensus, and polarization.

"The role of social networks is relatively paradoxical. On the one hand, the world is more interconnected, we have better access to information and different opinions," he notes. "But, on the other hand, we should not forget the fact that they can shape users' opinions on an unprecedented scale, giving rise to broad polarization. My goal was to find models to analyze this phenomenon and to use my experience with formal methods to adapt economic and statistical models that had already addressed similar problems."

The main objective of his model is to explain the phenomenon of belief formation under the effect of cognitive biases. He identifies three forms:

• The authority bias, or the tendency to be more easily influenced by the opinion of an authority figure or influencer.
• Confirmation bias, or the tendency to seek out, interpret, favor, and recall information that confirms or supports one's own prior beliefs or values.
• The reversal bias, whereby showing people evidence that proves them wrong is often ineffective, and can end up backfiring, causing them to defend their initial position even more strongly.

His model shows how this phenomenon can, in turn, lead to polarization, resulting in fractures within society. His results already show that social networks can be designed differently, adjusting algorithms for biases that will impact the flow of influence and thus produce different results, with less polarization.

The fact remains that often, regardless of the purpose of the discussion, some individuals derive pleasure from annoying others and that is the purpose of their activity. The algorithm may or may not make it easier for them.

For the full article: Social Networks: Can Mathematical Modeling Help Reduce Opinion Polarization?

A Multi-agent Model for Polarization Under Confirmation Bias in Social Networks - https://hal.archives-ouvertes.fr/hal-03095987

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