Decoding the apple paradox: a critical discourse analysis of gender, technology, and nationalism in China's digital space

The study investigates how gendered, nationalist, and technological discourses converge in China’s digital space following internet celebrity Xiang Ligang’s 2023 accusation that Apple deceived users about 5G signals on Beijing’s subway. In the ensuing debate—amplified amid the iPhone 15 launch and competition with Huawei’s Mate 60—consumer choice was elevated into a nationalist contest (Huawei-as-China vs. iPhone-as-U.S.). The authors note how this techno-nationalist framing became entangled with misogynistic portrayals of female iPhone users as lacking intelligence, morally suspect, and unpatriotic. Using Douyin (TikTok China), where the topic trended with massive engagement, the paper poses three research questions: (RQ1) How are images of female iPhone users shaped in Douyin video comments? (RQ2) What discursive strategies construct these images? (RQ3) How does this construction resonate with ongoing socio-political dynamics (e.g., techno-nationalism, state-sanctioned misogyny, platform algorithms) in China? The study’s purpose is to unpack these interlocking discourses and their implications for gender equality and digital culture in China.

The literature review situates the work at the intersection of techno-nationalism, gender, and digital discourse in China. It outlines how technology brands (e.g., Huawei, Apple) are nationalized and mobilized within Sino–U.S. techno-strategic narratives, often infused with masculinized nationalism (Enloe; Deckman & Cassese). Prior research examines Chinese digital nationalism but sparsely addresses its intersection with misogyny in consumer-tech contexts. The review traces post-reform gender politics: marketization, resurging patriarchal norms, and new masculinist anxieties; state ambivalence toward feminism and platform-enabled ‘state-sanctioned misogyny’; and global/networked misogyny patterns (e.g., Red Pill), adapted locally through Chinese digital cultures. Work on platformization highlights how algorithms, content moderation, and commercialization can amplify nationalist and misogynistic narratives. Studies on gendered nationalism (Nagel; Fang & Repnikova) and discourses around transnational marriages (Cheng) inform the paper’s analysis of how female tech consumers become ‘internal Others’ within nationalist frames.

Corpus compiling and data: The authors searched Douyin for the hashtag #项立刚质疑苹果5G造假 (#Xiang Ligang Questions Apple5G Fraud) and collected the 10 most applauded short videos. Using BaZhuaYu (Octopus) web crawler, they extracted comments, anonymized all data, and ensured compliance with Douyin/ByteDance policies (non-commercial academic use, privacy protection). After removing off-topic/promotional/emoji-only/@-only comments, the final corpus comprised 11,466 comments totaling 123,587 tokens. Preprocessing: Chinese segmentation via Gensim Jieba; multiple Chinese stopword lists (Library of Chinese Stop Words, HIT, Baidu, Sichuan Univ. Robot Intelligence Lab) plus custom domain dictionaries tailored to internet texts. Analytic framework: The study integrates Feminist Critical Discourse Analysis (FCDA; Lazar) within Fairclough’s three-dimensional CDA model (text description; discourse practice; socio-cultural practice). Discourse is also theorized via van Leeuwen’s recontextualization of social practice to analyze social actors/actions. To mitigate subjectivity and enhance representativeness, the authors adopt corpus-assisted discourse analysis (CADA), combining quantitative corpus methods with qualitative CDA. Corpus methods: Built a lexical co-occurrence network using Rostcm6 and visualized with Netdraw to identify key nodes around Apple/phones and gendered terms. Used Sketch Engine for keyword extraction, with Chinese Web Corpus (zhTenTen 2017) as reference; statistical tests identified top keywords (p<0.01). A focused sub-corpus (by querying 女/female; 妹/姐/sister) enabled analysis of bi-lexical/multiword pejoratives common in Chinese internet discourse (e.g., 女汉奸, KTV小姐, 女舔狗, 厂妹). Concordance analysis examined usage/contexts of salient terms such as 小姐 (prostitute), 舔狗 (simp), 厂妹 (factory girl), and 汉奸 (traitor). The analysis then interpreted how these linguistic patterns articulate cyber misogyny, economic stratification, and nationalism across Fairclough’s three levels.

- The Douyin corpus (11,466 comments; 123,587 tokens) around #Xiang Ligang Questions Apple5G Fraud reveals systematic derision of female iPhone users through sexualized, classed, and nationalist labels. - Lexical network: Central nodes (Apple/phone) connect to designators for women ranging from neutral to derogatory (e.g., ‘bargirl’, ‘prostitute’, ‘unsophisticated young woman’), alongside negative adjectives (‘garbage’, ‘ignorance’, ‘vanity’) and nightlife/service-industry terms (‘massage’, ‘nightclubs’, ‘entertainment venues’), indicating objectification and moralization. - Keyword analysis (sub-corpus focused on female referents) shows highly salient multiword pejoratives, including: 女汉奸 (female traitors), KTV小姐 (KTV bar prostitutes), 小姐姐机/夜店小姐专业 (prostitute’s phone/nightclub prostitute standard), 女舔狗 (female simp), 苹果女 (Apple female user), 厂妹 (factory girl), 陪酒女 (bar-girl), 夜场妹 (nightclub sister), 外国男人 (foreign men). These terms construct women as sexually immoral, low-status, and unpatriotic. - Three principal discursive formations: 1) Defamatory tactics: Women iPhone users are labeled as ‘prostitutes’, using sexism to police women’s behavior and justify surveillance/shaming. This reframes consumer choice as a moral failing and a deviation from national loyalty. 2) Class coding and threatened masculinity: The ‘factory girl’ trope and contrasts like ‘teachers/civil servants use Huawei’ vs. ‘KTV prostitutes/bartenders/factory girls use iPhones’ encode class hierarchies and certainty claims. The frequent use of ‘simp’ (舔狗) indicates male anxiety about emasculation and women’s consumer power. Market data cited suggest greater female affinity for premium iPhones vs. male preference for domestic brands, intensifying resentment. 3) Nationalistic guise: Misogynistic attacks are cast as patriotic defense; women buying foreign phones are framed as ‘traitors’ aligned with Western men/culture. This East–West binary legitimizes harassment as nationalism, displacing systemic issues onto women and reinforcing patriarchal control. - The analysis demonstrates a merger of digital misogyny, economic stratification, and techno-nationalism on Douyin, amplified by platform dynamics (algorithmic recommendations, engagement incentives) and a broader environment of state-endorsed nationalism.

The findings answer RQ1 by showing that female iPhone users are constructed as immoral (sex workers), low-status (‘factory girls’), irrational/vanity-driven, and disloyal (‘female traitors’). For RQ2, the strategies include sexualized slurs (小姐), classed stereotypes, othering via East–West binaries, populist anti-elite framing, and delegitimization through humor and certainty markers. The label ‘traitor’ converts consumer choice into a test of patriotism, legitimizing abuse as patriotic duty. For RQ3, these constructions resonate with China’s techno-nationalism, masculinized narratives of national identity, and state–platform dynamics that enable the circulation of nationalist content. Algorithmic amplification and monetized engagement on Douyin contribute to echo chambers where misogynistic-nationalist frames thrive. The discourse reflects broader post-reform gender politics—male status anxieties, resurging patriarchy, and stigmatization of feminism—showing how digital arenas both mirror and intensify gendered power relations under nationalist cover.

The study demonstrates how gendered, nationalist, and technological discourses converge on Chinese social media—especially Douyin—to denigrate female iPhone users as immoral, low-class, and unpatriotic. Methodologically, integrating FCDA with CADA and Fairclough’s model reveals how platformed discourse practices recontextualize social actors and actions to maintain patriarchal dominance. Empirically, the analysis identifies three interlocking formations—sexualized vilification, class-based derogation and threatened masculinity, and nationalist legitimation—that together politicize consumer tech choices as markers of allegiance. Contributions include (1) extending research on digital nationalism by detailing its gendered operation in consumer-tech contexts, (2) illustrating platform mechanisms that sustain networked misogyny within nationalist frames, and (3) offering a corpus-assisted, feminist discourse approach applicable to similar digital phenomena. Future research should (a) compare platforms and time periods to track discursive shifts, (b) examine platform governance and moderation impacts, (c) broaden datasets beyond top videos, and (d) assess interventions (algorithmic, policy, media literacy) that may disrupt misogynistic-nationalist echo chambers.