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Identifying issue frames in text.

Eyal Sagi1, Daniel Diermeier, Stefan Kaufmann

  • 1Kellogg School of Management, Northwestern University, Evanston, Illinois, United States of America. eyal@u.northwestern.edu

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|July 23, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a new corpus analysis method to quantify linguistic framing effects. The approach efficiently measures how context influences public opinion and tracks framing shifts over time.

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Area of Science:

  • Psychology
  • Public Opinion Research
  • Computational Linguistics

Background:

  • Framing, the influence of context on cognition, is a key area in psychology and public opinion research.
  • Traditional framing studies often use controlled experiments or manual document annotation, which are time-consuming and difficult to scale.
  • A need exists for efficient methods to analyze framing in large text datasets.

Purpose of the Study:

  • To present a novel corpus analysis method for quantifying the relative strengths of competing linguistic frames.
  • To develop a scalable and efficient approach requiring minimal human intervention for framing analysis.
  • To demonstrate the method's utility in tracking temporal framing shifts and comparing partisan framing.

Main Methods:

  • Corpus analysis to identify and quantify linguistic frames.
  • Development of a computational method for measuring frame strength.
  • Application to large text corpora for analyzing framing dynamics.

Main Results:

  • The proposed method effectively quantifies linguistic frame strengths with minimal human input.
  • Demonstrated ability to track changes in the framing of 'terror' over time.
  • Successfully compared the framing of 'abortion' between U.S. Democrats and Republicans.

Conclusions:

  • The corpus analysis method offers an efficient and scalable way to study framing effects.
  • This approach facilitates the analysis of framing in large-scale text data, advancing research in psychology and public opinion.
  • The findings highlight the dynamic nature of framing and its partisan divergence.