What
are the mechanisms and conditions that lead to such polarized political
landscapes as the one we live in today? In the article “Opinion polarization by learning from social feedback”,
which recently appeared in the Journal of Mathematical Sociology, Sven
Banisch and Eckehard Olbrich were able to explain the role of social
feedback in the phenomenon of polarization, using mathematical tools
from game theory.
We all react very sensitively to positive
or negative reactions from our peers and this feedback unconsciously
affects our own decision-making. In order to be able to understand and
identify mechanisms and conditions that lead to opinion polarization,
Sven Banisch and Eckehard Olbrich have presented a novel approach to
opinion dynamics which social feedback and reinforcement learning. The
results of their research have recently appeared in the Journal of
Mathematical Sociology.
Motivated by psychological
research on implicit processes of attitude change, the scientists have
studied a mathematical model where agents within a network evaluate
alternative views based on the received social feedback. After a
rigorous mathematical analysis, they were able to conclude that
feedback from peers may indeed explain why an initially moderate
population tends to polarize over time.
The authors propose a new paradigm based on reinforcement
learning, where opinions change in response to positive or negative
feedback. Disagreement among peers leads to decreased attachment to a
certain opinion and to a reevaluation of one’s position. On the
contrary, if an opinion favored by the agent gets the approval of the
social environment, this positive feedback reinforces the value
associated with this opinion. As a consequence of this feedback, an
initially already cohesive subgroup tends to become more and more
inclined towards an opinion over time and is more likely to align over
more extreme opinions, leading to the formation of opinion clusters.
This idea resonates with the concept of echo-chamber, a situation in
which beliefs are amplified or reinforced by communication and
repetition inside a closed system. This leads to a phenomenon that
scientists call gate-keeping: certain opinions are prevented from
spreading to another subgroup or cluster.
In their research, the
scientists have used models based on networks as well as game theoretic
notions to model the role of social feedback. More precisely, the
implementation of reinforcement learning naturally leads them to use the
tools of game theory, a branch of mathematics that studies interactions
between decision-making agents. Quite surprisingly, the equilibrium
points appearing in the system turned out to be equilibrium points in
the game-theoretical sense, giving further evidence for the robustness
of the model.
The authors also investigated which structural
features in a network lead to the appearance of polarization over time. A
rigorous analysis aided by the tools of game theory led them to show
that the
existence of opinion cohesive subgroups is a sufficient condition to generate stable polarization, even if
the subgroups one starts with have the chance to interact with each other.
This novel approach may explain the opinion polarization we observe in the political discourse today
and has the potential to improve on the existing approaches to opinion dynamics.
