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Sentence voice preferences and sentiment patterns in gendered Weibo headlines on violent events: A data-driven critical discourse analysis

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Data-driven analysis reveals gendered language differences in Weibo headlines about violence, indicating underlying biases.

This research aims to explore gendered language differences in Weibo headlines about violent events and their implications.
Utilized Fairclough’s Critical Discourse Analysis framework.
Conducted quantitative textual and sentiment analysis from 2021 to 2024 on Weibo hot-search topics.
Explored socio-cultural influences on language use in media.
Passive voice is preferred when men are perpetrators and women victims, highlighting female suffering.
No significant emotional differences by perpetrator gender were found in headlines.
The findings reflect traditional gender hierarchies and the media’s discursive stance.

Chen et al. (2026) studied this question.

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View Full Paper

Ask AI

Bookmark

Authors

Data-driven analysis reveals gendered language differences in Weibo headlines about violence, indicating underlying biases.

This research aims to explore gendered language differences in Weibo headlines about violent events and their implications.
Utilized Fairclough’s Critical Discourse Analysis framework.
Conducted quantitative textual and sentiment analysis from 2021 to 2024 on Weibo hot-search topics.
Explored socio-cultural influences on language use in media.
Passive voice is preferred when men are perpetrators and women victims, highlighting female suffering.
No significant emotional differences by perpetrator gender were found in headlines.
The findings reflect traditional gender hierarchies and the media’s discursive stance.

Chen et al. (2026) studied this question.

View Full Paper

Ask AI

Bookmark