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        <title>Gendered Stylistic Variation in Brazilian Portuguese Google Play Reviews: A Large-Scale Study</title>
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        <namePart type="given">Tiago</namePart>
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            <namePart type="family">Souza</namePart>
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            <namePart type="given">Iria</namePart>
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        <name type="personal">
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    <abstract>We study gender-associated stylistic variation in Brazilian Portuguese Google Play reviews. Using IBGE name frequencies, we infer binary gender from first names in 76.7M reviews (96 apps, 2011–2025), obtaining 22.25M high-confidence labels. Women-associated reviews show markedly higher paralinguistic expressivity (about 60% higher emoji density and more lengthening/punctuation), while lexical diversity (MTLD) is nearly identical across groups. Ratings are mostly positive, with men contributing relatively more 1-star reviews and women more 5-star reviews. These findings contribute to a deeper understanding of digital sociolinguistic behavior within the Brazilian context. We discuss limitations of name-based gender inference and future demographic extensions.</abstract>
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%0 Conference Proceedings
%T Gendered Stylistic Variation in Brazilian Portuguese Google Play Reviews: A Large-Scale Study
%A Melo, Tiago de
%Y Souza, Marlo
%Y de-Dios-Flores, Iria
%Y Santos, Diana
%Y Freitas, Larissa
%Y Souza, Jackson Wilke da Cruz
%Y Ribeiro, Eugénio
%S Proceedings of the 17th International Conference on Computational Processing of Portuguese (PROPOR 2026) - Vol. 2
%D 2026
%8 April
%I Association for Computational Linguistics
%C Salvador, Brazil
%@ 979-8-89176-387-6
%F melo-2026-gendered
%X We study gender-associated stylistic variation in Brazilian Portuguese Google Play reviews. Using IBGE name frequencies, we infer binary gender from first names in 76.7M reviews (96 apps, 2011–2025), obtaining 22.25M high-confidence labels. Women-associated reviews show markedly higher paralinguistic expressivity (about 60% higher emoji density and more lengthening/punctuation), while lexical diversity (MTLD) is nearly identical across groups. Ratings are mostly positive, with men contributing relatively more 1-star reviews and women more 5-star reviews. These findings contribute to a deeper understanding of digital sociolinguistic behavior within the Brazilian context. We discuss limitations of name-based gender inference and future demographic extensions.
%U https://aclanthology.org/2026.propor-2.32/
%P 238-246

Markdown (Informal)

[Gendered Stylistic Variation in Brazilian Portuguese Google Play Reviews: A Large-Scale Study](https://aclanthology.org/2026.propor-2.32/) (Melo, PROPOR 2026)

• Gendered Stylistic Variation in Brazilian Portuguese Google Play Reviews: A Large-Scale Study (Melo, PROPOR 2026)

ACL

• Tiago de Melo. 2026. Gendered Stylistic Variation in Brazilian Portuguese Google Play Reviews: A Large-Scale Study. In Proceedings of the 17th International Conference on Computational Processing of Portuguese (PROPOR 2026) - Vol. 2, pages 238–246, Salvador, Brazil. Association for Computational Linguistics.