Sexist Slurs: Reinforcing Feminine Stereotypes Online.
Social media platforms are accused repeatedly of creating environments in which women are bullied and harassed. We argue that online aggression toward women aims to reinforce traditional feminine norms and stereotypes. In a mixed methods study, we find that this type of aggression on Twitter is comm...
| Publicado en: | Sex Roles Vol. 83; no. 1/2; pp. 16 - 29 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Springer Nature
Jul2020
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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=143726177&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 143726177 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 03600025 SXR jtl: Sex Roles issn: 03600025 maglogo: N pubinfo: dt: Jul2020 vid: 83 iid: 1/2 pid: 237 pub: Springer Nature artinfo: ui: 143726177 10.1007/s11199-019-01095-z ppf: 16 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P size: 437KB tig: atl: Sexist Slurs: Reinforcing Feminine Stereotypes Online. aug: au: Felmlee, Diane Inara Rodis, Paulina Zhang, Amy affil: Department of Sociology and Criminology, Pennsylvania State University, 206 Oswald Tower, 16802, University Park, PA, USA Department of Statistics, Pennsylvania State University, 16802, University Park, PA, USA su: Twitter (Web resource) Discriminatory language Gender stereotypes Sexism Sexual harassment of women sug: subj: Discriminatory language Gender stereotypes Sexism Sexual harassment of women Twitter (Web resource) keyword: Beauty ideals Harassment Hostility toward women Online aggression Social media Social networks Stereotypes Victimization Beauty ideals Harassment Hostility toward women Online aggression Social media Social networks Stereotypes Victimization ab: Social media platforms are accused repeatedly of creating environments in which women are bullied and harassed. We argue that online aggression toward women aims to reinforce traditional feminine norms and stereotypes. In a mixed methods study, we find that this type of aggression on Twitter is common and extensive and that it can spread far beyond the original target. We locate over 2.9 million tweets in one week that contain instances of gendered insults (e.g., "bitch," "cunt," "slut," or "whore")—averaging 419,000 sexist slurs per day. The vast majority of these tweets are negative in sentiment. We analyze the social networks of the conversations that ensue in several cases and demonstrate how the use of "replies," "retweets," and "likes" can further victimize a target. Additionally, we develop a sentiment classifier that we use in a regression analysis to compare the negativity of sexist messages. We find that words in a message that reinforce feminine stereotypes inflate the negative sentiment of tweets to a significant and sizeable degree. These terms include those insulting someone's appearance (e.g., "ugly"), intellect (e.g., "stupid"), sexual experience (e.g., "promiscuous"), mental stability (e.g., "crazy"), and age ("old"). Messages enforcing beauty norms tend to be particularly negative. In sum, hostile, sexist tweets are strategic in nature. They aim to promote traditional, cultural beliefs about femininity, such as beauty ideals, and they shame victims by accusing them of falling short of these standards. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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