ZMT - Leibniz Zentrum für Marine Tropenforschung

ABSTRACT
Polarisation is a great concern in current social and political debates. A divergence of opinions or, more generally, a lack of societal agreement, for example on fundamental problems like climate change, presents a barrier to rapid action against a looming crisis. There are many theories on why people polarise on certain topics. However, the drivers of polarisation in social environments are multi-faceted and involve complex feedback among social, cognitive, and structural processes. While humans require interactions with each other to form shared views and cooperate effectively on many problems, social influence can produce a variety of opinion patterns, such as consensus, persistent disagreement, or polarisation.
In this thesis, I develop mathematical models of opinion formation or perception to uncover the conditions underpinning the emergence of different patterns. In particular, I formalise how psychological factors distort the way individuals perceive others into a mathematical language and analyse how these perceptions affect the formation of consensus or the persistence of disagreement in a virtual society. Each chapter focuses on a different factor. In Chapter 2, an interplay of ambiguity in communication and confirmation bias in information processing affects how individuals adapt their opinions to social influence. In Chapter 3, social identities and related in-group bias affect the degree to which individuals are influenced by others. In Chapter 4, peoples' subjective representations of the opinions of others change in time and, thereby, affect the degree of perceived polarisation.
The models rely on theoretical insights about social processes and, partly, on empirical data obtained from surveys about climate change opinions. Taken together, the three studies demonstrate that the factors distorting people's perceptions or responses to social influence---noise, bias, or subjective perception---have a non-negligible and sometimes surprising impact on collective opinion patterns. First, there is an optimal combination of moderate confirmation bias and moderate ambiguity in communication for a group to reach pro-environmental agreement (Chapter 2). Second, in-group bias typically strengthens disagreement between different social identity groups. But moderate in-group bias can also facilitate agreement when a society is characterised by a very dispersed interaction network. This surprising effect emerges because the bias increases the alignment within one in-group, thus accelerating the spread of an opinion across the dispersed network (Chapter 3). Third, individuals may perceive more ideological polarisation than actually exists when the way they represent the opinions of others is shaped by political identity groups and those groups become increasingly aligned. My analysis of survey data on climate-related opinions of German citizens shows that ideological polarisation on climate change may indeed be exaggerated. However, perceived polarisation varies greatly across political groups (Chapter 4).
This thesis demonstrates the importance of unravelling the mechanisms behind social phenomena and their non-trivial consequences on opinion dynamics. While the models and the conclusions presented in the thesis may not be readily used to predict opinion patterns, owing to the complexity and inherent uncertainty of our society, they contribute to the social sciences by demonstrating counter-intuitive consequences of seemingly obvious theoretical assumptions, highlighting gaps and potentially critical ambiguities in social theories, and suggesting future directions for empirical analysis.