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Opinion-based group membership as a predictor of collective emotional responses and support for pro- and anti-war action

Musgrove, L. and McGarty, C. (2008) Opinion-based group membership as a predictor of collective emotional responses and support for pro- and anti-war action. Social Psychology, 39 (1). pp. 37-47.

Link to Published Version: http://dx.doi.org/10.1027/1864-9335.39.1.37
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Abstract

Social identity theory, intergroup emotions theory (IET), and related approaches offer the potential to understand the social psychological aspects of collective behavior such as movements that protest against or argue for war. Social identification, however, tends to be a weak predictor of collective action intentions. We argue that in order to understand the fault lines of collective action it is useful to consider identification with opinion-based groups. We illustrate this in relation to support for and opposition to the war on terror (WoT) in Australia. Comparing predictions based on IET with those based on opinion-based group identification, we found limited support for the sets of connections hypothesized by IET. Alternatively, social identification with pro- and anti-WoT opinion-based groups was a strong predictor of different emotional reactions and associated action intentions. In particular, highly identified supporters of the WoT were angry at terrorists, and this anger in turn predicted offensive action tendencies against the terrorists. Stronger yet were the emotional reactions of anger at the government reported by highly identified opponents of the WoT, which strongly predicted anti-war protest action intentions. The results point to the utility of the opinion-based group concept for understanding the collective, yet contested, aspects of political support for war and peace in contemporary society.

Publication Type: Journal Article
Murdoch Affiliation: School of Psychology
Publisher: Hogrefe & Huber Publishers
Copyright: Hogrefe & Huber Publishers
URI: http://researchrepository.murdoch.edu.au/id/eprint/3148
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