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Understanding how political attention is divided and over what subjects is crucial for research on areas such as agenda setting, framing, and political rhetoric. Existing methods for measuring attention, such as manual labeling according to established codebooks, are expensive and can be restrictive. We describe two computational models that automatically distinguish topics in politicians' social media content. Our models---one supervised classifier and one unsupervised topic model---provide different benefits. The supervised classifier reduces the labor required to classify content according to pre-determined topic list. However, tweets do more than communicate policy positions. Our unsupervised model uncovers both political topics and other Twitter uses (e.g., constituent service). These models are effective, inexpensive computational tools for political communication and social media research. We demonstrate their utility and discuss the different analyses they afford by applying both models to the tweets posted by members of the 115th U.S. Congress.
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Measuring Agenda Setting in Interactive Political Communication
Although strategies exist to measure actors' efforts to set policy, media, and lawmaking agendas, political scientists lack a method for identifying and accurately measuring another form of agenda setting that lies under the surface anytime two people talk. Within interactions, such as debates, deliberations, and discussions, actors can set the agenda by shifting others' attention to their preferred topics. In this article, I use a topic model that locates where topic shifts occur within an interaction in order to measure the relative agenda-setting power of actors. Validation exercises show that the model accurately identifies topic shifts and infers coherent topics. Three empirical applications also validate the agenda-setting measure within different political settings: U.S. presidential debates, in-person deliberations, and online discussions. These applications show that successfully setting the agenda can shape an interaction's outcomes, demonstrating the importance of continued research on this form of agenda setting.
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- Award ID(s):
- 1938811
- PAR ID:
- 10297835
- Date Published:
- Journal Name:
- American Journal of Political Science
- ISSN:
- 0092-5853
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1111/ajps.12653
