To examine Chinese public discourse on breast cancer using sentiment analysis and topic modeling on data collected from Sina Weibo.
Approach:
Methodology: Utilized sentiment analysis and topic modeling to analyze Weibo posts related to breast cancer, focusing on emotional expression and thematic content.
Key Findings:
Social media, particularly Weibo, serves as a vital platform for public discourse on breast cancer, facilitating information sharing and support.
Existing studies on breast cancer discourse have primarily focused on Western platforms, with limited research on Eastern contexts like Chinese social media.
Interpretation:
The study highlights the need for comprehensive analysis of social media discourse on breast cancer, particularly in non-Western contexts, to understand public sentiments and educational impacts.
Limitations:
Existing literature lacks big-data investigations of Chinese public discourse on breast cancer.
Previous studies have not integrated text mining with social cognitive perspectives for deeper analysis.
Conclusion:
The findings emphasize the importance of utilizing Weibo data to explore public attitudes and emotional responses regarding breast cancer in China.
