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In:The Construction of ‘Ordinariness’ across Media Genres
Edited by Anita Fetzer and Elda Weizman
[Pragmatics & Beyond New Series 307] 2019
► pp. 21–50

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Are Austrian presidential candidates ordinary people?

Candidates’ self-presentation strategies on Twitter during the 2016 Austrian presidential election campaign

 | University of Vienna, Austria
Published online: 12 December 2019
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https://doi.org/10.1075/pbns.307.02gru
Abstract
This paper investigates one specific aspect of impression management (self-presentation as an ordinary person) of the candidates during the 2016 Austrian presidential campaign on Twitter and asks whether the candidates’ campaigns followed the innovation or the normalization hypothesis. By applying Goffman’s concepts of “giving” vs. “giving off” information to the affordances of political communication on Twitter, a communicated ordinariness strategy is distinguished from a staged ordinariness strategy. Different forms of these two strategies are identified in the candidates’ tweets by investigating the pictorial and verbal elements of their tweets. Results show that both strategies are employed rather infrequently in all but one of the candidates’ tweets. Only one of the candidates used a staged ordinariness strategy during one phase of the campaign. These results show that most candidates employed communication strategies which conform to the normalization hypothesis rather than to the innovation hypothesis. Furthermore, the results suggest that following a consistent communication strategy throughout an entire campaign might ultimately lead to electoral success.
Article outline
  • 1.Introduction
  • 2.Doing “being an ordinary person” on social media platforms
  • 3.Data and campaign details
  • 4.Methodology
  • 5.Results
    • 5.1Frequency of picture use in candidates’ tweets
    • 5.2Qualitative aspects of the politicians’ visual impression management strategies
    • 5.3Indicators of staged ordinariness
  • 6.Discussion and conclusions
  • Notes
  • References
References (33)
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This list is based on CrossRef data as of 28 november 2025. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.

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