Framing Gender Through Words: Examining Stereotypical Language in AI-Generated News Headlines on TikTok

Abstract

The increased integration of artificial intelligence in the development of digital news has had a significant impact on how information is concluded and consumed on social media platforms. TikTok, in particular, has become an important platform for the spread of information in the form of news, for which short videos accompany AI-generated headlines, which have a strong impact on the interpretation of the audience. This study examines the frame of gender in cases of AI-generated news headlines in TikTok and analyses whether the automated texts replicate stereotypical gender depictions. Employing a qualitative content analysis of 100 TikTok videos published from 2023-24, the study examines the insistent stability of lexic patterns in the headlines with the subjects (male vs. female) in particular manifesting certain aspects like authority, achievement, emotional framing, appearance, and relational identity. The results show the presence of clear and systematic gender asymmetries: Headlines of men apparently focus mainly on competence, agency, and professional accomplishment, while those of women more often foreground emotional states, physical appearance, and familial or relational roles. These patterns suggest AIs will not only reflect age-old gender issues in traditional news media, but they can actually exacerbate these issues in algorithmically led but engagement-optimised institutions. The study concludes that the unchecked acceptance of AI-generated language in the social media space for news content runs the risk of perpetuating gendered hierarchies as well as highlighting the need for more critical oversight in AI-assisted news content.

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