“She’ll Never Be a Man” A Corpus-Based Forensic Linguistic Analysis of Misgendering Discrimination on X

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AEIWETJT7" target="_blank" >RIV/00216208:11320/25:EIWETJT7 - isvavai.cz</a>

Result on the web

<a href="https://www.mdpi.com/2226-471X/9/9/291" target="_blank" >https://www.mdpi.com/2226-471X/9/9/291</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/languages9090291" target="_blank" >10.3390/languages9090291</a>

Result language

angličtina

Original language name

“She’ll Never Be a Man” A Corpus-Based Forensic Linguistic Analysis of Misgendering Discrimination on X

Original language description

Misgendering is a form of microaggression that reinforces gender binarism and involves the use of incorrect pronouns, names or gendered language when referring to a transgender and gender non-conforming (TGNC) individual. Despite growing awareness, it remains a persistent form of discrimination, and it is crucial not only to understand and address misgendering but also to analyse its impact within online discourse towards the TGNC community. The present study examines misgendering directed at the TGNC community present on platform X. To achieve this, a representative sample of 400 tweets targeting two TGNC individuals is compiled, applying an annotation scheme to manually classify the polarity of each tweet and instances of misgendering, and then comparing the manual annotations with those of an automatic sentiment detection system. The analysis focuses on the context and frequency of intentional misgendering, using word lists to examine the data. The results confirm that misgendering perpetuates discrimination, tends to co-occur with other forms of aggression, and is not effectively identified by automatic sentiment detection systems. Finally, the study highlights the need for improved automatic detection systems to better identify and address misgendering in online discourse and provides potentially useful tools for future research.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

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Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Languages

ISSN

2226-471X

e-ISSN

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Volume of the periodical

9

Issue of the periodical within the volume

9

Country of publishing house

US - UNITED STATES

Number of pages

20

Pages from-to

1-20

UT code for WoS article

001323539000001

EID of the result in the Scopus database

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