# SWSR: A Chinese Dataset and Lexicon for Online Sexism Detection

arXiv: https://arxiv.org/abs/2108.03070 · HTML: https://mlsanity.com/paper/2108.03070/

## Key facts

- Cited by 42 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 70 references that are in the map.
- First posted on arXiv 6 Aug 2021.

## Builds on (most cited first, 12 of 12)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Convolutional Neural Networks for Sentence Classification](https://mlsanity.com/paper/1408.5882/) (2014)
- [Directions in Abusive Language Training Data: Garbage In, Garbage Out](https://mlsanity.com/paper/2004.01670/) (2020)
- ["Call me sexist, but...": Revisiting Sexism Detection Using Psychological Scales and Adversarial Samples](https://mlsanity.com/paper/2004.12764/) (2020)
- [Confronting Abusive Language Online: A Survey from the Ethical and Human Rights Perspective](https://mlsanity.com/paper/2012.12305/) (2020)
- [Developing a Multilingual Annotated Corpus of Misogyny and Aggression](https://mlsanity.com/paper/2003.07428/) (2020)
- [Ginger Cannot Cure Cancer: Battling Fake Health News with a Comprehensive Data Repository](https://mlsanity.com/paper/2002.00837/) (2020)
- [GILE: A Generalized Input-Label Embedding for Text Classification](https://mlsanity.com/paper/1806.06219/) (2018)
- [Multi-label Categorization of Accounts of Sexism using a Neural Framework](https://mlsanity.com/paper/1910.04602/) (2019)
- [Let-Mi: An Arabic Levantine Twitter Dataset for Misogynistic Language](https://mlsanity.com/paper/2103.10195/) (2021)
- [Fortifying Toxic Speech Detectors Against Veiled Toxicity](https://mlsanity.com/paper/2010.03154/) (2020)

## Built on by (most cited first, 30 of 42)

- [COLD: A Benchmark for Chinese Offensive Language Detection](https://mlsanity.com/paper/2201.06025/) (2022)
- [Facilitating Fine-grained Detection of Chinese Toxic Language: Hierarchical Taxonomy, Resources, and Benchmarks](https://mlsanity.com/paper/2305.04446/) (2023)
- [Towards Identifying Social Bias in Dialog Systems: Frame, Datasets, and Benchmarks](https://mlsanity.com/paper/2202.08011/) (2022)
- [Rethinking Machine Ethics -- Can LLMs Perform Moral Reasoning through the Lens of Moral Theories?](https://mlsanity.com/paper/2308.15399/) (2023)
- [ToxiCloakCN: Evaluating Robustness of Offensive Language Detection in Chinese with Cloaking Perturbations](https://mlsanity.com/paper/2406.12223/) (2024)
- [MultiHateClip: A Multilingual Benchmark Dataset for Hateful Video Detection on YouTube and Bilibili](https://mlsanity.com/paper/2408.03468/) (2024)
- [An Investigation of Large Language Models for Real-World Hate Speech Detection](https://mlsanity.com/paper/2401.03346/) (2024)
- [CORGI-PM: A Chinese Corpus For Gender Bias Probing and Mitigation](https://mlsanity.com/paper/2301.00395/) (2023)
- [Multilingual and Explainable Text Detoxification with Parallel Corpora](https://mlsanity.com/paper/2412.11691/) (2024)
- [Lost in Pronunciation: Detecting Chinese Offensive Language Disguised by Phonetic Cloaking Replacement](https://mlsanity.com/paper/2507.07640/) (2025)
- [Subjective textitIsms? On the Danger of Conflating Hate and Offence in Abusive Language Detection](https://mlsanity.com/paper/2403.02268/) (2024)
- [OpenEval: Benchmarking Chinese LLMs across Capability, Alignment and Safety](https://mlsanity.com/paper/2403.12316/) (2024)
- [STATE ToxiCN: A Benchmark for Span-level Target-Aware Toxicity Extraction in Chinese Hate Speech Detection](https://mlsanity.com/paper/2501.15451/) (2025)
- [Re-examining Sexism and Misogyny Classification with Annotator Attitudes](https://mlsanity.com/paper/2410.03543/) (2024)
- [A Graph-Based Context-Aware Model to Understand Online Conversations](https://mlsanity.com/paper/2211.09207/) (2022)
- [SCCD: A Session-based Dataset for Chinese Cyberbullying Detection](https://mlsanity.com/paper/2501.15042/) (2025)
- [Chinese Offensive Language Detection:Current Status and Future Directions](https://mlsanity.com/paper/2403.18314/) (2024)
- [Unified Game Moderation: Soft-Prompting and LLM-Assisted Label Transfer for Resource-Efficient Toxicity Detection](https://mlsanity.com/paper/2506.06347/) (2025)
- [Examining Temporal Bias in Abusive Language Detection](https://mlsanity.com/paper/2309.14146/) (2023)
- [ChineseWebText 2.0: Large-Scale High-quality Chinese Web Text with Multi-dimensional and fine-grained information](https://mlsanity.com/paper/2411.19668/) (2024)
- [OutSafe-Bench: A Benchmark for Multimodal Offensive Content Detection in Large Language Models](https://mlsanity.com/paper/2511.10287/) (2025)
- [SexWEs: Domain-Aware Word Embeddings via Cross-lingual Semantic Specialisation for Chinese Sexism Detection in Social Media](https://mlsanity.com/paper/2211.08447/) (2022)
- [Cross-lingual Offensive Language Detection: A Systematic Review of Datasets, Transfer Approaches and Challenges](https://mlsanity.com/paper/2401.09244/) (2024)
- [Divided by discipline? A systematic literature review on the quantification of online sexism and misogyny using a semi-automated approach](https://mlsanity.com/paper/2409.20204/) (2024)
- [PANDA -- Paired Anti-hate Narratives Dataset from Asia: Using an LLM-as-a-Judge to Create the First Chinese Counterspeech Dataset](https://mlsanity.com/paper/2501.00697/) (2025)
- [Chinese Toxic Language Mitigation via Sentiment Polarity Consistent Rewrites](https://mlsanity.com/paper/2505.15297/) (2025)
- [Cracking the Code: Enhancing Implicit Hate Speech Detection through Coding Classification](https://mlsanity.com/paper/2506.04693/) (2025)
- [Fine-Grained Chinese Hate Speech Understanding: Span-Level Resources, Coded Term Lexicon, and Enhanced Detection Frameworks](https://mlsanity.com/paper/2507.11292/) (2025)
- [Exploring the Capability Boundaries of LLMs in Mastering of Chinese Chouxiang Language](https://mlsanity.com/paper/2604.15841/) (2026)
- [HausaNLP at SemEval-2023 Task 10: Transfer Learning, Synthetic Data and Side-Information for Multi-Level Sexism Classification](https://mlsanity.com/paper/2305.00076/) (2023)

## Abstract (arXiv)

Online sexism has become an increasing concern in social media platforms as it has affected the healthy development of the Internet and can have negative effects in society. While research in the sexism detection domain is growing, most of this research focuses on English as the language and on Twitter as the platform. Our objective here is to broaden the scope of this research by considering the Chinese language on Sina Weibo. We propose the first Chinese sexism dataset -- Sina Weibo Sexism Review (SWSR) dataset --, as well as a large Chinese lexicon SexHateLex made of abusive and gender-related terms. We introduce our data collection and annotation process, and provide an exploratory analysis of the dataset characteristics to validate its quality and to show how sexism is manifested in Chinese. The SWSR dataset provides labels at different levels of granularity including (i) sexism or non-sexism, (ii) sexism category and (iii) target type, which can be exploited, among others, for building computational methods to identify and investigate finer-grained gender-related abusive language. We conduct experiments for the three sexism classification tasks making use of state-of-the-art machine learning models. Our results show competitive performance, providing a benchmark for sexism detection in the Chinese language, as well as an error analysis highlighting open challenges needing more research in Chinese NLP. The SWSR dataset and SexHateLex lexicon are publicly available.