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Description: Public opinion is often considered as an aggregation of preferences, but the field has the potential to be much richer. For decades, scholars have argued for the value of going beyond measuring political preferences and examining how individuals reason about and justify those preferences. However, this task has only recently become tractable with the emergence of modern computational methods. In this paper, I present a text-based approach for inferring characteristics of individuals’ political reasoning. This method identifies the key concepts a person raises and examines the implicit connections between those concepts – what ideas are connected to which other ideas? This structural approach is theoretically justified in both the cognitive and linguistic literatures, which repeatedly suggest that humans store, retrieve, and interpret information through network structures. I show that this approach provides insight into the quality of a person’s reasoning and reveals meaningful individual variation which is correlated with known behavioral traits. The ability to measure and interrogate individuals’ expressions of political reasoning holds the potential to shed new light on the dynamics of public opinion and political behavior. Questions of persuasion, ideological fracturing, and conversation quality all rely upon understanding individual styles of political expression. These dynamics are driven not just by what someone says but by how they say it.


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