Techno-semiotic resistance

A multimodal analysis of anti-surrogacy image-mediated commentary in Chinese digital discourse

Bibliographic Data

ID7750804
AuthorsJingshen Ge (0000-0002-0621-1277, Ocean University of China, Qingdao, Shandong, China), Weiqi Tian (0000-0002-6913-2461, Xinjiang University, Wulumuqi, Xinjiang Uygur Autonomous Region, China, corresponding author)
Year2025
Publication date2025-09-11
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueDiscourse Studies (JOURNAL)
Journal identifiersISSN: 1461-4456 • E-ISSN: 1461-7080
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/14614456251366472
OpenAlexW4414121211
LanguageEN
Citations received1
References cited44

This paper conducts an in-depth analysis of anti-surrogacy image-mediated commentary (IMC) on Chinese social media through a multimodal social semiotic approach, highlighting how users creatively engage with digital platforms. The study reveals a predominance of text-oriented image-mediated commentary employing verbal anchorage against simplistic visual backgrounds, strategically enhancing the impact of anti-surrogacy narratives. These image-mediated commentaries serve as powerful tools for identity construction, with users assuming roles such as Mobilizers and Feminist Celebrators, fostering a dynamic interaction that strengthens community cohesion and advocacy strategies. Nonetheless, the research identifies radical feminist ideologies that focus on women’s victimhood, while simultaneously critiquing the image-mediated commentaries’ limitations in target specificity and systemic critique. The findings illuminate the complex interplay of digital resistance and ideological discourse, advancing our understanding of image-mediated commentary culture as a potent site for digital activism. This study invites future cross-cultural research into rhetorical strategies and their implications for global social movements

Discourse analysis · Discursive psychology · Ideology · Multimodality · Rhetorical question · Semiotics · Gender, Feminism, and Media · Hate Speech and Cyberbullying Detection · Media, Gender, and Advertising

Tools

Open DOI