A Corpus-based Study of Sexist Language in the Hashtag #everydaysexism on Twitter

Abstract

This paper examines the Twitter hashtag #everydaysexism as the discourse of sexist language about the digital feminist movement, focusing on the fourth wave of feminism. Twitter users use #everydaysexism to "shouting back" and expose their experiences relating to sexism in daily life. The corpora consist of 1118 tweets in the hashtag #everydaysexism that include all the English tweets posted within 12 months (from April 1, 2020, until March 31, 2021). After conducting a thematic analysis using Melville et al.'s (2019) model, this topic work/office/company/customer has an overwhelming share, with 24.14% being overt and 75.86% indirect sexism. This result supported Mills' (2008) argument, namely, indirect sexism is relatively easier to articulate these days in formal contexts. Drawing on Mills’ (2008) sexist language framework, this study then concludes by analyzing the different sexist language markers to reflect some issues regarding gender differences and to signal people to think about their behaviour and speech.



Author Information
Wanwen Wang, Hong Kong Metropolitan University, Hong Kong

Paper Information
Conference: BAMC2021
Stream: Linguistics

This paper is part of the BAMC2021 Conference Proceedings (View)
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Posted by amp21