  Despite the considerable efforts being made to monitor and regulate
user-generated content on social media platforms, the pervasiveness of
offensive language, such as hate speech or cyberbullying, in the digital space
remains a significant challenge. Given the importance of maintaining a
civilized and respectful online environment, there is an urgent and growing
need for automatic systems capable of detecting offensive speech in real time.
However, developing effective systems for processing languages such as Chinese
presents a significant challenge, owing to the language's complex and nuanced
nature, which makes it difficult to process automatically. This paper provides
a comprehensive overview of offensive language detection in Chinese, examining
current benchmarks and approaches and highlighting specific models and tools
for addressing the unique challenges of detecting offensive language in this
complex language. The primary objective of this survey is to explore the
existing techniques and identify potential avenues for further research that
can address the cultural and linguistic complexities of Chinese.
