‘I just don’t think she has a presidential look:’ the influence of sexism on candidate image

ABSTRACT

Facebook and other social media are often utilized by political campaigns to communicate with the electorate and provide vital information about a candidate. However, in doing so, political campaigns and their audiences are open to unfavorable comments, including sexism and misogyny. The current experiment investigates the influence of sexist Facebook comments on candidate support in a hypothesized moderated mediation process. Through manipulating the discussion beneath a Facebook post providing candidate information about a female candidate, we distinguish the influence of sexist comments from issue-based and pro-female commentary. We find evidence suggesting both pro-female and sexist commentary impact evaluation of a hypothetical female candidate through image scores and homophily. The social media discussion affects both image evaluations of the candidate and feelings of homophily, which lead to an increase in support for the female candidate.

KEYWORDS:

• Sexism
• social media
• political campaigns
• online discussion
• female candidates

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Freddie J. Jennings PhD, is a Visiting Assistant Professor at the University of Arkansas. His research focuses on cognition and persuasion, social identification, and political communication in an evolving media landscape [email: [email protected]]

Calvin R. Coker PhD, is an Assistant Professor – Term at the University of Louisville. His research program focuses on the way marginalized populations are represented in politics [email:[email protected]]

Notes

1 There is a body of scholarship (e.g., Bracic, Israel-Trummel, & Shortle, 2019; Sanbonmatsu 2002; Strolovitch et al. 2017) which suggests that sexist preferences play a role in evaluation of a candidate. However, as the present study focused on social identity, homophily, and identification, the presence of measures evaluating sexism would have likely introduced measurement error via social desirability.