Sentiment analysis of cancer screening in Chinese social media: Qualitative studies based on machine learning

PURPOSE: Explore public perceptions and sentiments about cancer screening on social media. The dissemination of misinformation and negative attitudes continue to impede the access of many individuals with perceived risk to cancer screening services despite their awareness of the necessity and concept of early cancer screening. METHODS: This study was divided into five steps: data collection, data cleaning, data standardization, sentiment analysis, and content analysis. RESULTS: This study analyzed 796 social media comments (53,151 words) from Weibo, Zhihu, and Xiaohongshu to explore public sentiments toward cancer screening. Seven emotion categories emerged: good, happy, surprise, anger, disgust, fear, and sadness. Positive emotions reflected trust in physicians, financial support, and perceived screening effectiveness, whereas negative emotions reflected fear of cancer, stigma, and procrastination. CONCLUSION: The findings of this study include the development of health communication strategies, the promotion of public screening participation, and the improvement of nursing personalization and emotional sensitivity. These findings highlight barriers and facilitators for cancer screening promotion in China and inform targeted nursing communication strategies.