The beliefs we hold are shaped by a complex interaction between our internal thoughts and the external environment. A recent study employs established principles from statistical physics to explore various dimensions of belief dynamics. This comprehensive method may provide innovative strategies for addressing real-world issues such as increased polarization or the dissemination of false information.
The beliefs we hold are shaped through a complicated interplay of our internal thoughts and our external circumstances. Our individual thinking and our connections with others come together to form our understanding of the world and affect our readiness to change these views in light of new information. Historically, research has examined these two levels of belief separately: psychologists have focused on the cognitive processes at the personal level, while experts in computational social science and statistical physics have explored how beliefs evolve within societies.
Jonas Dalege, a former SFI Complexity Postdoctoral Fellow and current Marie Curie Fellow at the University of Amsterdam, states, “This divide in efforts across disciplines impedes advancement.”
In a paper released on September 19 in Psychological Review, Dalege and his co-authors introduce the Networks of Beliefs theory, which merges individual and social belief dynamics while also factoring in societal perceptions: how individuals view the beliefs held by those around them.
“A key aspect of our model focuses on perceptions,” Dalege explains. “You can never fully grasp what someone thinks. For example, if you strongly identify as a Democrat, you may presume that your friends share that belief, and it might take considerable effort to alter those assumptions.”
The Networks of Beliefs theory “distinctly identifies personal, social, and external dissonances,” according to the authors. “To truly comprehend when and why individuals alter their beliefs, we must investigate how these dissonances collectively drive different social behaviors.”
This theory revolves around three core concepts.
The first concept posits that beliefs can be visualized as two interrelated network types: internal and external. The internal network encompasses a range of associated beliefs — for example, a person’s beliefs about vaccines may connect to their views on science, economics, and religion — including social beliefs. The external network illustrates the relationship between someone’s social beliefs and another individual’s actual beliefs.
The second concept asserts that individuals seek to minimize dissonance among their beliefs, whether at a personal, social, or external level. Personal dissonance occurs when one holds conflicting beliefs, such as believing both in the efficacy and the risks of vaccines. Social dissonance arises from discrepancies between what a person believes and what they think their peers think. External dissonance is experienced when a person’s perceptions of others’ beliefs do not align with those beliefs.
The third concept states that the level of dissonance experienced by a person is influenced by how much attention they dedicate to the inconsistencies in their beliefs. This attention can differ based on individual and cultural dispositions and the subject in question.
The authors drew parallels with statistical physics to formulate a quantitative model for their theory. Co-author and researcher at the Complexity Science Hub in Austria, Henrik Olsson, mentions, “We align psychological ideas with concepts from statistical physics. We regard potential dissonance as energy and attention as temperature, enabling us to leverage known statistical physics frameworks to depict the intricate dynamics of belief networks.”
The Networks of Beliefs theory enables researchers to examine the interactions between individual beliefs and those of their social circles, alongside actual versus perceived beliefs and varying levels of attention. Furthermore, it elucidates how beliefs shift when we focus on different elements of our belief systems.
“At times, we might concentrate more on our personal dissonance to ensure our beliefs resonate with our values,” asserts SFI Professor Mirta Galesic, another co-author and researcher at Complexity Science Hub. “Other times, particularly in socially sensitive contexts, we may tune in more to the discrepancies between our beliefs and those of others. In those situations, we might adjust our beliefs to align with perceived social expectations.”
The model, validated through two extensive surveys, holds potential applications for various real-world challenges. For example, it could serve as a new approach to counteracting rising polarization globally. “To effectively understand and address polarization, we need to expand our view beyond just individual or social perspectives,” Dalege highlights. “Incomplete solutions can lead to harmful policies that might yield the opposite outcomes we’re aiming for.”
