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Self-ie love: Predictors of image editing intentions on Facebook

Lowe-Calverley, EJ ORCID: 0000-0002-0865-2404 and Grieve, R ORCID: 0000-0002-5211-4179 2018 , 'Self-ie love: Predictors of image editing intentions on Facebook' , Telematics and Informatics, vol. 35, no. 1 , pp. 186-194 , doi: 10.1016/j.tele.2017.10.011.

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Little research has examined image-editing behaviour on social media, yet with images being a key form of online social communication, the importance of such research is evident. The aim of the current study was to examine the factors that influence peoples’ intentions to post digitally altered self-images on the Facebook platform, using an extended Theory of Planned Behaviour (TPB) model. It was hypothesised that after controlling for age, prior editing application use, and integration of Facebook in a user’s life, the TPB variables (attitudes, subjective norms, and perceived behavioural control [PBC]) would explain a significant proportion of intention to post digitally altered images on Facebook. Furthermore, that the addition of narcissism would explain further variation in intentions, beyond that explained by the control and TPB variables. Participants (N = 151; Mage = 25.6 years; 76% female) completed an online survey assessing each of the aforementioned variables. Hierarchical multiple regression revealed that each of the hypotheses were supported, with all variables significantly contributing to the prediction of intentions, except PBC and age. This study sheds light on the predictors of image-editing behaviour, and sets the stage for subsequent research examining editing behaviours on Facebook as well as other social media platforms (e.g. Instagram).

Item Type: Article
Authors/Creators:Lowe-Calverley, EJ and Grieve, R
Keywords: Facebook; Image editing; Selfie; Social media; Theory of Planned Behaviour; Narcissism
Journal or Publication Title: Telematics and Informatics
Publisher: Pergamon Press
ISSN: 0736-5853
DOI / ID Number: 10.1016/j.tele.2017.10.011
Copyright Information:

Copyright 2017 Elsevier Ltd.

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