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Narrative warmth and quantitative competence: Message type affects impressions of a speaker

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  • Jenna L Clark
  • Melanie C Green
  • Joseph J P Simons

Abstract

Persuasion research often focuses on how source characteristics affect attitude change in response to a message; however, message characteristics may also alter perceptions of the source. The Message-Based Impression Formation effect (M-BIF) suggests that perceivers use features of messages to infer characteristics of the source, and that such inferences may have a variety of consequential outcomes. In particular, the choice of narrative versus statistical evidence may have implications for the perceived warmth and competence of a source. In five experiments, narrative arguments led to greater perceptions of source warmth and statistical arguments led to greater perceptions of source competence. Across the two behavioral studies, a matching effect emerged: participants preferred to work on cooperative tasks with partners who had provided narratives, and competitive tasks with partners who had provided statistical evidence. These results suggest that the evidence type chosen for everyday communications may affect person perception and interpersonal interaction.

Suggested Citation

  • Jenna L Clark & Melanie C Green & Joseph J P Simons, 2019. "Narrative warmth and quantitative competence: Message type affects impressions of a speaker," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-21, December.
  • Handle: RePEc:plo:pone00:0226713
    DOI: 10.1371/journal.pone.0226713
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    References listed on IDEAS

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    1. Angela Fagerlin & Brian J. Zikmund-Fisher & Peter A. Ubel & Aleksandra Jankovic & Holly A. Derry & Dylan M. Smith, 2007. "Measuring Numeracy without a Math Test: Development of the Subjective Numeracy Scale," Medical Decision Making, , vol. 27(5), pages 672-680, September.
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