
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.
Facebook, 330, Impression management, Self-presentation, Politics, Political engagement, 320, political engagement, Social networking sites, social networking sites, politics, self-presentation
Facebook, 330, Impression management, Self-presentation, Politics, Political engagement, 320, political engagement, Social networking sites, social networking sites, politics, self-presentation
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 46 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
