Please use this identifier to cite or link to this item:
https://repositorio.consejodecomunicacion.gob.ec//handle/CONSEJO_REP/12481| Title: | Partisan Self-Stereotyping: Testing the Salience Hypothesis in a Prediction of Political Polarization |
| Other Titles: | International Journal of Communication |
| Authors: | Han, Jiyoung Wackman, Daniel |
| Keywords: | conflict framing identity |
| Issue Date: | 2017 |
| Publisher: | International Journal of Communication |
| Citation: | Han, J. and Wackman, D. (2017). Partisan Self-Stereotyping: Testing the Salience Hypothesis in a Prediction of Political Polarization. International Journal of Communication, 11. https://ijoc.org/index.php/ijoc/article/view/5533/1922 |
| Abstract: | The goal of this study is to theorize the relationship between the news and political polarization through a lens of group dynamics. Consistent with the salience hypothesis of the category fit and category accessibility interaction, we first articulate when and how news exposure makes news consumers think of themselves as Democrats or Republicans instead of unique individuals. Drawing on group polarization literature, we further hypothesize partisan self-stereotyping—an automatic reaction to partisan identity salience—as a mechanism behind the polarizing effect of partisan conflict-framed news. Two experimental studies provide a consistent pattern of support for our hypotheses. The implications of these findings were discussed in comparison with extant studies testing similar news effects under a different theoretical framework—namely, motivated reasoning. |
| URI: | https://repositorio.consejodecomunicacion.gob.ec//handle/CONSEJO_REP/12481 |
| ISSN: | 1932-8036 |
| Appears in Collections: | Documentos internacionales sobre libertad de expresión y derechos conexos |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| ojsadmin,+5533-19284-13-ED.pdf | Partisan Self-Stereotyping: Testing the Salience Hypothesis in a Prediction of Political Polarization | 1,04 MB | Adobe PDF | View/Open |
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