Our paper on the Causal Attitude Network (CAN) model was published in Psychological Review (PDF).
In the paper, we introduce the CAN model, which conceptualizes attitudes as networks consisting of interacting evaluative reactions, such as beliefs (e.g., judging a presidential candidate as competent and charismatic), feelings (e.g., feeling proudness and hope about the candidate), and behaviors (e.g., voting for the candidate). Interactions arise through direct causal connections between the evaluative reactions (e.g., feeling hopeful about the candidate because one judges her as competent and charismatic). The CAN model assumes that causal connections between evaluative reactions serve to heighten the consistency of the attitude and we argue that the Ising model’s axiom of energy expenditure reduction represents a formalized account of consistency pressure. Because individuals not only strive for consistency but also for accuracy, network representations of attitudes have to deal with the tradeoff between consistency and accuracy. This tradeoff is likely to lead to a small-world structure and we show that attitude networks indeed have a small-world structure. We also discuss the CAN model’s implication for attitude change and stability. Furthermore, we show that connectivity of attitude networks provides a formalized and parsimonious account of the dynamical differences between strong and weak attitudes.