The Portrayal of Men and Women in Digital Communication: Content Analysis of Gender Roles and Gender Display in Reaction GIFs.
This article explores gender roles and gender displays in animated GIFs. The 747 most popular reaction GIFs accessible via Tenor, Giphy, and Gfycat were content analyzed. An automated approach using machine learning and a human coding approach were used to code for primary characters. Findings revea...
| Publicado en: | International Journal of Communication (19328036) Vol. 15; pp. 462 - 493 |
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| Autores principales: | , , |
| Formato: | Artículo |
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University of Southern California, USC Annenberg Press
2021
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=152907031&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 152907031 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 19328036 3836 jtl: International Journal of Communication (19328036) issn: 19328036 maglogo: N pubinfo: dt: 2021 vid: 15 pid: 16336 pub: University of Southern California, USC Annenberg Press artinfo: ui: 152907031 ppf: 462 ppct: 31 formats: tig: atl: The Portrayal of Men and Women in Digital Communication: Content Analysis of Gender Roles and Gender Display in Reaction GIFs. aug: au: ÁLVAREZ, DIEGO GONZÁLEZ, ALEJANDRO UBANI, CRISTINA affil: Universitat Politècnica de València, Spain. Basque Government, Spain. su: Digital communications Instant messaging Graphics interchange format Machine learning Computer programming sug: subj: Digital communications Instant messaging Other Computer Related Services Custom Computer Programming Services Computer systems design and related services (except video game design and development) Graphics interchange format Machine learning Computer programming keyword: gender display gender representation nonverbal behavior instant messaging reaction GIF gender display gender representation nonverbal behavior instant messaging reaction GIF ab: This article explores gender roles and gender displays in animated GIFs. The 747 most popular reaction GIFs accessible via Tenor, Giphy, and Gfycat were content analyzed. An automated approach using machine learning and a human coding approach were used to code for primary characters. Findings revealed that female characters were underrepresented in comparison to their counterparts. Across the age groups, women appeared younger than men. Compared with male figures, females were more prone to be portrayed as slightly nude, wearing sexually revealing clothing, and sometimes in attire considered unsuitable for the context of the situation. In contrast, chi-square analyses indicated no significant differences between genders in terms of nonverbal behaviors (“displays”) such as expression of emotions, smiling, or gazing, and use of gestures. The results of sentiment analysis in reaction GIFs’ titles showed no different sentiment scores for GIFs depicting either male or female main characters. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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