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Cited by 178

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Inoculation in Political Campaign Communication

Open access
PFAU, MICHAEL, BURGOON, MICHAEL·1988·Human Communication Research

Abstract

The use of attack messages in political campaign communication has grown in recent years. This investigation posits a strategy of resistance to the influence of attack messages. A total of 341 initial and follow-up treatment interviews and 392 control interviews were completed among potential voters in a U.S. Senate campaign during October 1986. We hypothesized that political campaign messages can be designed to inoculate supporters of candidates against subsequent attack messages of opposing candidates. This prediction was supported. In addition, the results supported the hypothesis that inoculation confers more resistance to subsequent attack messages among strong political party identifiers as opposed to weak identifiers, non-identifiers, and crossovers. The results of this investigation extend the scope of inoculation theory to new domain, and at the same time, suggest a new strategic approach for candidates in political campaigns.

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Crossref · 10.1111/j.1468-2958.1988.tb00172.x

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Metadata

Authors
PFAU, M., & BURGOON, M.
Venue
Human Communication Research
Published
1988-09
Volume
15
Issue
1
Pages
91-111
ISSN
  • 0360-3989 (ISSN-L)
  • 1468-2958
OpenAlex
W2003018734
Cited by
178
References
2
FWCI
26.65
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Inoculation in Political Campaign Communication. https://app.cochat.ai/papers/10.1111/j.1468-2958.1988.tb00172.x
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PFAU, M., & BURGOON, M. (1988). Inoculation in Political Campaign Communication. Human Communication Research. https://doi.org/10.1111/j.1468-2958.1988.tb00172.x

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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.