You can access my dissertation here.
Attitudes are immensely complex – they are formed through several different processes, are sometimes impactful and durable, yet in other instances inconsequential and fluctuating, and are at the core of central psychological constructs. Given this complexity, a rigorous formal approach to attitudes might seem out of reach. However, recent developments in complexity science have shown that complex behavior often emerges from simple lower level processes (e.g., the complex behavior of a flock of birds emerges from simple rules followed by each bird). Using analogical modeling, this thesis develops formalisms on the central dynamics of attitude. These formalisms are inspired by work in complexity science, network science, and statistical mechanics. The approach of this thesis rests on a small number of assumptions. First, attitudes can be conceptualized as a network of mutually influencing beliefs (e.g., judging a person as nice and honest), feelings (e.g., affection towards this person), and behaviors (e.g., spending much time with this person) vis-à-vis an attitude object. Second, the influence between these different attitude elements increases with the amount of attention and thought directed at the attitude object. Based on these assumptions I develop a general theory on attitude that explains several well-established phenomena in the attitude literature. Additionally, I provide empirical tests on some core predictions of the formalisms developed in this thesis. I conclude that these formalisms not only provide the building blocks for a theory of attitude, but can also serve as a blueprint for the dynamics of mental representations in general.