17,161 research outputs found

    Examining Self-Presentation Efforts to Create Instagram Posts

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    This item is only available electronically.Research suggests that individuals engage in effortful behaviours to self-present when posting on Instagram. However, these Instagram preparatory behaviours (IPB) (e.g. editing, photo-selection, asking friends for feedback), have not yet been examined in detail. The aims of the study were to (1) describe the diverse range of IPB individuals may engage in and (2) investigate the psychological processes that may be associated with IPB. Goffman’s (1990) impression management (IM) theory was employed to conceptualise IPB as a process whereby users attempt to control others’ perceptions of their Instagram profiles. A convenience sample of 135 participants completed an online survey investigating IM, gender, contingent self-worth (appearance and others’ approval), perfectionistic self-presentation and perfectionistic hiding effort. Unexpectedly, the results showed that men and women did not differ significantly in terms of IPB. IPB was positively correlated with all independent variables apart from gender. A multiple regression found that IM and perfectionistic self-presentation were significant positive predictors of IPB. The findings provide support for Goffman’s (1990) theory of “backstage” effortful behaviours in pursuit of IM “front stage” and suggest that perfectionism is implicated in IPB. These findings propose that IPB may become problematic when undertaken excessively for self-image goals and perfectionistic striving. Keywords: Instagram, self-presentation, effort, impression management, perfectionismThesis (B.PsychSc(Hons)) -- University of Adelaide, School of Psychology, 201

    Tagvisor: A Privacy Advisor for Sharing Hashtags

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    Hashtag has emerged as a widely used concept of popular culture and campaigns, but its implications on people's privacy have not been investigated so far. In this paper, we present the first systematic analysis of privacy issues induced by hashtags. We concentrate in particular on location, which is recognized as one of the key privacy concerns in the Internet era. By relying on a random forest model, we show that we can infer a user's precise location from hashtags with accuracy of 70% to 76%, depending on the city. To remedy this situation, we introduce a system called Tagvisor that systematically suggests alternative hashtags if the user-selected ones constitute a threat to location privacy. Tagvisor realizes this by means of three conceptually different obfuscation techniques and a semantics-based metric for measuring the consequent utility loss. Our findings show that obfuscating as little as two hashtags already provides a near-optimal trade-off between privacy and utility in our dataset. This in particular renders Tagvisor highly time-efficient, and thus, practical in real-world settings

    #unfollow on Instagram Factors that have an impact on the decision to unfollow public figures

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    The social media platform Instagram allows users to subscribe to various people from their immediate circle of acquaintances or to follow public figures. Recent research has identified reasons concerning the discontinuance of social media use and the unfollowing behaviour on certain social media platforms. However, little is known about the unfollowing behaviour on Instagram and what causes users to unfollow public figures in particular. This study was the first trying to find out what factors influence users between the ages of 20 and 29 years of age to unfollow public figures. To this end, a total of nine qualitative guideline interviews were conducted with users recruited via Instagram. The interviews were analysed by means of an summary qualitative content analysis. Thereby, a total of eleven factors could be identified. The first factor relates to the negative feelings that arise when the content is received. The second and third factors relate to the public figure: behaviour and communication. The fourth, fifth and sixth factors relate to the frequency of posts, stories and the same content. The seventh, eighth, ninth, tenth and eleventh factors relate to content, but in different aspects: advertising, design, lack of identification, unfulfilled expectations and changes.The social media platform Instagram allows users to subscribe to various people from their immediate circle of acquaintances or to follow public figures. Recent research has identified reasons concerning the discontinuance of social media use and the unfollowing behaviour on certain social media platforms. However, little is known about the unfollowing behaviour on Instagram and what causes users to unfollow public figures in particular. This study was the first trying to find out what factors influence users between the ages of 20 and 29 years of age to unfollow public figures. To this end, a total of nine qualitative guideline interviews were conducted with users recruited via Instagram. The interviews were analysed by means of an summary qualitative content analysis. Thereby, a total of eleven factors could be identified. The first factor relates to the negative feelings that arise when the content is received. The second and third factors relate to the public figure: behaviour and communication. The fourth, fifth and sixth factors relate to the frequency of posts, stories and the same content. The seventh, eighth, ninth, tenth and eleventh factors relate to content, but in different aspects: advertising, design, lack of identification, unfulfilled expectations and changes
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