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Cited by 249

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The Interaction of News and Advocate Frames: Manipulating Audience Perceptions of a Local Public Policy Issue

Tewksbury, David, Jones, Jennifer, Peske, Matthew W., Raymond, Ashlea, Vig, William·2000·Journalism & Mass Communication Quarterly

Abstract

This article presents the results of a two-wave experiment designed to examine how journalistic news frames can facilitate the communication of advocacy frames designed to influence audience perceptions of a political issue. We constructed five versions of a newspaper article about large-scale hog farms. The versions differed in the weight they gave to frames promoted by organizations interested in this issue. The relative emphasis given the competing frames was reflected in subjects' interpretations of the issue and in their evaluations of hog farms. A retest three weeks after the initial exposure revealed a significant, though muted, cognitive impact of the frames. The implications of these results for journalism, issue advocacy, and the study of issue framing are discussed.

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Metadata

Authors
Tewksbury, D., Jones, J., Peske, M. W., Raymond, A., & Vig, W.
Venue
Journalism & Mass Communication Quarterly
Published
2000-12
Volume
77
Issue
4
Pages
804-829
ISSN
  • 1077-6990 (ISSN-L)
  • 2161-430X
OpenAlex
W2111804971
Cited by
249
References
0
FWCI
4.05
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The Interaction of News and Advocate Frames: Manipulating Audience Perceptions of a Local Public Policy Issue. https://app.cochat.ai/papers/10.1177/107769900007700406
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Tewksbury, D., Jones, J., Peske, M. W., Raymond, A., & Vig, W. (2000). The Interaction of News and Advocate Frames: Manipulating Audience Perceptions of a Local Public Policy Issue. Journalism & Mass Communication Quarterly. https://doi.org/10.1177/107769900007700406

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.