Abstract: Online social networks have become increasingly popular as a means of social communication and sharing information in the digital era. The growing demand for social interaction has resulted in the spread of fake news on social media platforms. The depth and wide scope of the harm of fake news have made its detection one of the hot research topics in natural language processing. The article first introduces the relevant concepts and issues of fake news, then reviews methods for detecting fake news based on internal and external characteristics. It points out that fake news detection still faces challenges in real-time detection, data acquisition, class imbalance, and the spread of old rumors. Future research should focus on enhancing real-time fake news detection, multimodal and interpretable fake news detection, as well as multilingual and cross-cultural fake news detection.