Danielle L Paddock, Beth T Bell, Jennifer Cassarly
{"title":"\"OMG you look amazing\": A systematic examination of the text-based interactions surrounding UK adolescent girls' self-images on Instagram.","authors":"Danielle L Paddock, Beth T Bell, Jennifer Cassarly","doi":"10.1016/j.bodyim.2024.101839","DOIUrl":null,"url":null,"abstract":"<p><p>Appearance-related content is ubiquitous across highly visual social media platforms, in both imagery and text. The present study aims to explore the content of text-based interactions initiated by self-images on Instagram. Seventeen adolescent girls from the UK (Age M = 15.12; SD = 1.80; Range = 12-18) provided data from their most recent Instagram posts (up to 10 posts) as part of one-to-one interviews. This included images (n = 85), captions (n = 85), direct comments on images (n = 630) and participants' first replies to direct comments (n = 459). An inductive-deductive content analysis was used to analyse Instagram data, and a template analysis was used to analyse the interview data to aid with the interpretation of the content. Analyses showed positive appearance-related compliments were highly prevalent on Instagram posts (79.2 % of comments) and were considered the norm. Compliments tended to focus on general, rather than specific appearance qualities. Girls tended to respond to compliments using likes, gratitude, or affectionate expressions. The findings highlight the role of self-objectification and self-presentation strategies in dictating the norms of adolescent girls' text-based interactions on Instagram. Implications and directions for future research are discussed.</p>","PeriodicalId":48312,"journal":{"name":"Body Image","volume":"52 ","pages":"101839"},"PeriodicalIF":5.2000,"publicationDate":"2024-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Body Image","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1016/j.bodyim.2024.101839","RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHIATRY","Score":null,"Total":0}
引用次数: 0
Abstract
Appearance-related content is ubiquitous across highly visual social media platforms, in both imagery and text. The present study aims to explore the content of text-based interactions initiated by self-images on Instagram. Seventeen adolescent girls from the UK (Age M = 15.12; SD = 1.80; Range = 12-18) provided data from their most recent Instagram posts (up to 10 posts) as part of one-to-one interviews. This included images (n = 85), captions (n = 85), direct comments on images (n = 630) and participants' first replies to direct comments (n = 459). An inductive-deductive content analysis was used to analyse Instagram data, and a template analysis was used to analyse the interview data to aid with the interpretation of the content. Analyses showed positive appearance-related compliments were highly prevalent on Instagram posts (79.2 % of comments) and were considered the norm. Compliments tended to focus on general, rather than specific appearance qualities. Girls tended to respond to compliments using likes, gratitude, or affectionate expressions. The findings highlight the role of self-objectification and self-presentation strategies in dictating the norms of adolescent girls' text-based interactions on Instagram. Implications and directions for future research are discussed.
期刊介绍:
Body Image is an international, peer-reviewed journal that publishes high-quality, scientific articles on body image and human physical appearance. Body Image is a multi-faceted concept that refers to persons perceptions and attitudes about their own body, particularly but not exclusively its appearance. The journal invites contributions from a broad range of disciplines-psychological science, other social and behavioral sciences, and medical and health sciences. The journal publishes original research articles, brief research reports, theoretical and review papers, and science-based practitioner reports of interest. Dissertation abstracts are also published online, and the journal gives an annual award for the best doctoral dissertation in this field.