This project studies framing, a central concept in political communication that refers to portraying an issue from one perspective with corresponding de-emphasis of competing perspectives. Framing is known to significantly influence public attitudes toward policy issues and policy outcomes. As social media allow greater citizen engagement in political discourse, scientific study of the political world requires reliable analysis of how issues are framed, not only by traditional media and elites but by citizens participating in public discourse. Yet conventional content analysis for frame discovery and classification is complex and labor-intensive. Additionally, existing methods are ill-equipped to capture those many instances when one frame evolves into another frame over time.

This project therefore develops new computational modeling methods, grounded in data-driven computational linguistics, aimed at improving the scientific understanding of how issues are framed by political elites, the media, and the public. This collaboration between political scientists and computer scientists has four goals: (a) developing novel methods for semi-automated frame discovery, whereby computational models guided by political scientists? expert knowledge speed up and augment their analytical process; (b) developing novel algorithms based on natural language processing for automatic frame analysis, producing measurably accurate results comparable with reliable human coders; (c) establishing the validity of these processes on well-understood cases; and (d) applying these methods to several current policy issues, using data across years and across traditional and social media streams. The resulting evolutionary framing data will help unpack the mechanisms of framing and help predict trends in public opinion and policy.

Agency
National Science Foundation (NSF)
Institute
Division of Information and Intelligent Systems (IIS)
Type
Standard Grant (Standard)
Application #
1211266
Program Officer
William Bainbridge
Project Start
Project End
Budget Start
2012-10-01
Budget End
2016-09-30
Support Year
Fiscal Year
2012
Total Cost
$199,782
Indirect Cost
Name
University of California Davis
Department
Type
DUNS #
City
Davis
State
CA
Country
United States
Zip Code
95618