This study conducts an in-depth analysis of English comments in a cross-cultural environment by integrating topic models and sentiment analysis techniques. The research focuses on review data collected from users in the United States, China, India, and Germany from online platforms, utilizing the Latent Dirichlet Allocation (LDA) model and dictionary-based sentiment analysis methods. The results show that there are significant differences in the comment topics and emotional tendencies of users in different countries. For example, American reviewers discuss technology and life-related topics more frequently and express more positive emotions, while Chinese reviewers express more neutral emotions on economic and health topics. In addition, the analysis of the correlation between emotional intensity and topics reveals the emotional responses that specific topics may cause in different cultures. These findings provide insights into understanding consumer behavior in the context of globalization and are of great significance for optimizing international marketing strategies.