A study on identification of youth identity through a gender lens in network buzzwords: A critical discourse analysis

The proliferation of internet users in China has transformed cyberspace into a significant symbolic system, with network buzzwords acting as key indicators of youth mentality and identity. While buzzwords profoundly influence social reality, research on their interplay with gender formations remains limited. This study addresses this gap by focusing on gender-specific buzzwords, exploring how young people linguistically construct their identities within sociocultural contexts. The research questions guiding this study are: 1) How do young people construct identities through gender-specific buzzwords? 2) What types of youth identities, emphasizing gender, are reflected? 3) What are the ideological implications of using these buzzwords on Weibo? The increasing prevalence of gender-nonconforming youth in China highlights the urgency of this research, as the study seeks to understand how online discourse reinforces or challenges existing gender norms and stereotypes.

The study grounds its analysis in social identity theory, which posits that identity is constructed through language within social, cultural, and historical contexts. It highlights the two components of social identity theory: personal and social identity. The three steps involved in creating a social identity—classification, identification, and comparison—are discussed. The literature review also examines existing research on online buzzwords in China. While studies have analyzed buzzwords like *yizu* (ant tribe) and *diaosi* (penis thread), focusing on aspects like group preference and social commentary, research exploring gender-specific buzzwords remains scarce. Existing gender studies on buzzwords have focused on limited examples, such as "leftover women" and "big heroines", failing to offer a broader analysis.

This study uses purposive sampling to select 11 gender-specific buzzwords from the annual Top-Ten Network Buzzwords list published by *Yaowen Jiaozi* magazine from 2012 to 2021. The selection of *Yaowen Jiaozi* is justified by its independent status, release of diverse buzzwords, and significant influence. The buzzwords were categorized into class, gender, and lifestyle categories using NVivo 12 Pro software, achieving high inter-rater reliability (0.98). The researchers used Weibo posts containing these buzzwords to analyze how young people use them to construct identity. A post from the most recent three months (before April 17th, 2023) with the highest number of likes was selected for each buzzword. Data were analyzed using Fairclough's three-dimensional critical discourse analysis (CDA) framework (text, discourse practice, and sociocultural practice), supplemented by Wodak's concept of discursive strategies, particularly nomination. Back-translation was employed to ensure accurate interpretation of the Chinese text.

The analysis reveals that Weibo users utilize the nomination strategy to construct and distinguish identities. Buzzwords like *bai fu mei* (white, rich, beautiful) and *gao fu shuai* (tall, rich, handsome) project ideal partner identities, but simultaneously objectify individuals, reducing their worth to physical attributes and social status. The use of metaphors is also prevalent; for example, *lücha biao* (green tea bitch) negatively labels women perceived as manipulative, while *xiao xianrou* (little fresh meat) and *xiao gongju* (little princess) commodify young men and women respectively, reducing them to their attractiveness. The buzzword *nü hanzi* (female man) presents an oxymoron, representing both societal acceptance and self-awareness of contradicting traits. The analysis explores how terms of address like *lao ge* (old brother), *xiao gege* (little big brother), and *xiao jiejie* (little big sister) are used to denote affection, admiration, and even romantic interest, potentially reinforcing gender hierarchy. The buzzword *jimei* (gathered beauty) fosters a sense of female solidarity, whereas *shabaitian* (silly, white, and sweet) negatively stereotypes women as naive. The discourse practice analysis highlights how buzzwords are created in cyberspace and spread through social circles, from individual to collective identity. The sociocultural practice analysis reveals that most buzzwords (9/11) reflect gender conformity, reinforcing traditional gender roles and expectations, while a minority (2/11) display gender nonconformity, challenging these norms. The resistance, however, is often a moderate negotiation rather than outright confrontation.

The findings highlight the complex interplay between language, gender, and identity construction in the online space. The use of network buzzwords reveals how young people both reinforce and challenge prevailing gender norms. The prevalent use of gender-conforming buzzwords reflects the persistence of traditional gender roles and stereotypes in Chinese society. However, the presence of gender-nonconforming buzzwords suggests a degree of resistance and negotiation. The study demonstrates how seemingly harmless online language can contribute to the perpetuation of harmful stereotypes and reinforces existing power imbalances. The use of CDA provides valuable insights into the subtle ways language shapes and reflects societal attitudes toward gender. The study’s findings contribute to a deeper understanding of the role of online discourse in shaping youth identities in China and offer implications for media studies, gender studies, and sociolinguistics.

This study offers a novel contribution to the understanding of how network buzzwords construct youth identity through a gender lens. It reveals the complex interplay of gender conformity and nonconformity in online discourse, highlighting the subtle ways language perpetuates and challenges traditional gender roles. The research suggests that future studies could explore different online platforms and investigate cross-cultural variations in the use of network buzzwords to construct gendered identities.

The study is limited by its focus on Weibo data and a specific selection of buzzwords. The sample size, while sufficient for the current analysis, might not be fully representative of all young people in China. Furthermore, the reliance on back-translation could introduce some degree of interpretation bias. Future studies could investigate a larger and more diverse sample of Weibo posts and other platforms to enhance the generalizability of the findings.