Optimizing Social Media Public Opinion Analysis with ABSA: A Case Study on Weibo

Social media serves as a focal point for expressing opinions, making it crucial to understand the dynamics and content of public opinion for purposes such as online marketing and sentiment steering. This study applies Aspect-Based Sentiment Analysis (ABSA) to social media text analysis, utilizing extracted comment objects as aspects. Through the application of deep learning models, the research endeavors to capture the multifaceted sentiments of netizens towards various objects, juxtaposing the outcomes with conventional sentiment analysis methods. The findings reveal that ABSA, with its focus on research objects, excels in meticulous sentiment extraction, illustrating sentiment nuances, and accommodating special events in public sentiment analysis.