From Platform Migration to Cultural Integration: the Ingress and Diffusion of #wlw from TikTok to RedNote in Queer Women Communities

• URL: http://arxiv.org/abs/2508.07579v2
• Date: Tue, 12 Aug 2025 05:21:48 GMT
• Title: From Platform Migration to Cultural Integration: the Ingress and Diffusion of #wlw from TikTok to RedNote in Queer Women Communities
• Authors: Ziqi Pan, Runhua Zhang, Jiehui Luo, Yuanhao Zhang, Yue Deng, Xiaojuan Ma,
• Abstract summary: The Western-origin #wlw (women-loving-women) hashtag has risen in the Chinese lesbian community on RedNote.<n>This event provides a unique lens to study cross-cultural hashtag ingress and diffusion.<n>Results indicate that the successful introduction of #wlw was facilitated by TikTok immigrants' bold importation.
• Score: 28.812285243094355
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Hashtags serve as identity markers and connection tools in online queer communities. Recently, the Western-origin #wlw (women-loving-women) hashtag has risen in the Chinese lesbian community on RedNote, coinciding with user migration triggered by the temporary US TikTok ban. This event provides a unique lens to study cross-cultural hashtag ingress and diffusion through the populations' responsive behaviors in cyber-migration. In this paper, we conducted a two-phase content analysis of 418 #wlw posts from January and April, examining different usage patterns during the hashtag's ingress and diffusion. Results indicate that the successful introduction of #wlw was facilitated by TikTok immigrants' bold importation, both populations' mutual interpretation, and RedNote natives' discussions. In current manifestation of diffusion, #wlw becomes a RedNote-recognized queer hashtag for sharing queer life, and semantically expands to support feminism discourse. Our findings provide empirical insights for enhancing the marginalized communities' cross-cultural communication.

Related papers

• Discipline and Resistance: The Construction of a Digital Home for TikTok Refugees on Xiaohongshu [0.7499722271664147]
  This study examines how TikTok refugees moved to Xiaohongshu after TikTok was about to be banned in the United States.<n>It utilizes Foucault's idea of heterotopia to demonstrate how Xiaohongshu became a crisis space for cross-cultural discussions.
  arXiv  Detail & Related papers  (2025-07-19T03:47:55Z)
• From Flowers to Fascism? The Cottagecore to Tradwife Pipeline on Tumblr [0.9374652839580183]
  We collected and analyzed social media posts to investigate aesthetic-based radicalization where users searching for Cottagecore content may find Tradwife content co-opted by white supremacists, white nationalists, or other far-right extremist groups.<n>We found that problematic Tradwife posts found in the literature may be confined to Tradwife-only spaces, while content in the Cottagecore tag generally did not warrant extra moderation.<n>In our qualitative analysis there was more interaction between queer and Tradwife identities than expected based on the literature, and some Tradwives even explicitly included queer people and disavowed racism in the Tradwife community on Tumblr
  arXiv  Detail & Related papers  (2025-05-07T16:50:58Z)
• Temporal Analysis of Drifting Hashtags in Textual Data Streams: A Graph-Based Application [2.94944680995069]
  We analyze hashtag drifts over time using concepts from graph analysis and textual data streams. Our approach can be useful for monitoring changes over time in opinions and sentiment patterns about an entity on social media. The year 2021 was the most significant drifting year, in which the communities detected and their respective sizes suggest that #mybodymychoice had a significant drift to vaccination and Covid-19-related topics.
  arXiv  Detail & Related papers  (2024-02-08T21:58:53Z)
• RIGHT: Retrieval-augmented Generation for Mainstream Hashtag Recommendation [76.24205422163169]
  We propose RetrIeval-augmented Generative Mainstream HashTag Recommender (RIGHT) RIGHT consists of three components: 1) a retriever seeks relevant hashtags from the entire tweet-hashtags set; 2) a selector enhances mainstream identification by introducing global signals; and 3) a generator incorporates input tweets and selected hashtags to directly generate the desired hashtags. Our method achieves significant improvements over state-of-the-art baselines. Moreover, RIGHT can be easily integrated into large language models, improving the performance of ChatGPT by more than 10%.
  arXiv  Detail & Related papers  (2023-12-16T14:47:03Z)
• Exploring Gender-Based Toxic Speech on Twitter in Context of the #MeToo movement: A Mixed Methods Approach [2.454909090258064]
  The # movement has catalyzed widespread public discourse surrounding sexual harassment and assault, empowering survivors to share their stories and holding perpetrators accountable. While the movement has had a substantial and largely positive influence, this study aims to examine the potential negative consequences in the form of increased hostility against women and men on the social media platform Twitter. By analyzing tweets shared between October 2017 and January 2020 by more than 47.1k individuals who had either disclosed their own sexual abuse experiences on Twitter or engaged in discussions about the movement, we identify the overall increase in gender-based hostility towards both women and men since the start of the movement.
  arXiv  Detail & Related papers  (2023-08-24T20:45:12Z)
• Russo-Ukrainian War: Prediction and explanation of Twitter suspension [47.61306219245444]
  This study focuses on the Twitter suspension mechanism and the analysis of shared content and features of user accounts that may lead to this. We have obtained a dataset containing 107.7M tweets, originating from 9.8 million users, using Twitter API. Our results reveal scam campaigns taking advantage of trending topics regarding the Russia-Ukrainian conflict for Bitcoin fraud, spam, and advertisement campaigns.
  arXiv  Detail & Related papers  (2023-06-06T08:41:02Z)
• Black or White but never neutral: How readers perceive identity from yellow or skin-toned emoji [90.14874935843544]
  Recent work established a connection between expression of identity and emoji usage on social media. This work asks if, as with language, readers are sensitive to such acts of self-expression and use them to understand the identity of authors.
  arXiv  Detail & Related papers  (2021-05-12T18:23:51Z)
• Gender bias in magazines oriented to men and women: a computational approach [58.720142291102135]
  We compare the content of a women-oriented magazine with that of a men-oriented one, both produced by the same editorial group over a decade. With Topic Modelling techniques we identify the main themes discussed in the magazines and quantify how much the presence of these topics differs between magazines over time. Our results show that the frequency of appearance of the topics Family, Business and Women as sex objects, present an initial bias that tends to disappear over time.
  arXiv  Detail & Related papers  (2020-11-24T14:02:49Z)
• Demographic Representation and Collective Storytelling in the Me Too Twitter Hashtag Activism Movement [17.672730162091526]
  The # movement on Twitter has drawn attention to the pervasive nature of sexual harassment and violence. We examine online # conversations across gender and racial/ethnic identities. We find that tweets authored by white women were overrepresented in the movement compared to other demographics.
  arXiv  Detail & Related papers  (2020-10-13T15:25:33Z)
• Racism is a Virus: Anti-Asian Hate and Counterspeech in Social Media during the COVID-19 Crisis [51.39895377836919]
  COVID-19 has sparked racism and hate on social media targeted towards Asian communities. We study the evolution and spread of anti-Asian hate speech through the lens of Twitter. We create COVID-HATE, the largest dataset of anti-Asian hate and counterspeech spanning 14 months.
  arXiv  Detail & Related papers  (2020-05-25T21:58:09Z)
• Echo Chambers on Social Media: A comparative analysis [64.2256216637683]
  We introduce an operational definition of echo chambers and perform a massive comparative analysis on 1B pieces of contents produced by 1M users on four social media platforms. We infer the leaning of users about controversial topics and reconstruct their interaction networks by analyzing different features. We find support for the hypothesis that platforms implementing news feed algorithms like Facebook may elicit the emergence of echo-chambers.
  arXiv  Detail & Related papers  (2020-04-20T20:00:27Z)
• #MeToo on Campus: Studying College Sexual Assault at Scale Using Data Reported on Social Media [71.74529365205053]
  We analyze the influence of the # trend on a pool of college followers. The results show that the majority of topics embedded in those # tweets detail sexual harassment stories. There exists a significant correlation between the prevalence of this trend and official reports on several major geographical regions.
  arXiv  Detail & Related papers  (2020-01-16T18:05:46Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.