Purpose/Significance To evaluate and study the quality of information published by users of internet medical platforms using text content analysis method. Method/Process The text content of typical internet medical platforms in China is obtained by Python crawler, natural language processing (NLP) and clustering analysis are performed. Feature indexes are extracted and logistic regression model and grey relational degree correction are designed to construct an information quality evaluation index system. Result/Conclusion The information release and presentation of internet medical platforms can be strengthened from the aspects of information richness, characteristics of information publishers and user interaction, and users can be guided to release high-quality information and quickly identify valuable information, so as to promote the sustainable development of internet medical platforms.