“I like them, but won’t ‘Like’ them”: an examination of impression management associated with visible political party affiliation on Facebook

Marder, Ben and Slade, Emma and Houghton, David and Archer-Brown, Chris (2016) “I like them, but won’t ‘Like’ them”: an examination of impression management associated with visible political party affiliation on Facebook. Computers in Human Behaviour, 61. ISSN Unknown

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Official URL: http://dx.doi.org/10.1016/j.chb.2016.03.047

Abstract / Summary

Unlike traditional media, our interactions with political parties via social media are generally public, subject to scrutiny by others and, consequently, a self-presentation concern. This paper contributes to theory on impression management within social network sites (SNSs) by providing an understanding of the effect of visible affiliation on page ‘Liking’ behavior in the context of political parties; specifically, the possible association with social anxiety and the use of protective impression management. We predict that while users may be motivated to ‘Like’ a political party, some may feel socially anxious about the impressions their friends may derive from this action, and so ultimately choose to refrain from ‘Liking’ the party. Furthermore, we propose a new function of ‘Secret Likes’ (i.e. ‘Likes’ that others cannot see) as a means to increase gateway interactions. A survey of eligible voters (n=225) was conducted in the month prior to the 2015 UK general election, examining behavior associated with the Facebook pages of the two largest political parties. Results support that conspicuous affiliation with political parties indeed hinders intention to ‘Like’ political pages and is associated with social anxiety. ‘Secret Likes’ were found to be a successful method to increase gateway interactions. In addition to the theoretical contribution, implications for political party communications and site designers are considered.

Item Type: Article
Identification Number: doi.org/10.1016/j.chb.2016.03.047
ISSN: Unknown
Subjects: Business
Computer Science, Information & General Works
Technology
Related URLs:
Depositing User: Chris Archer-Brown
Date Deposited: 13 Mar 2018 10:44
Last Modified: 13 Mar 2018 10:44
URI: http://repository.falmouth.ac.uk/id/eprint/2809

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