Subtopic-Level Sentiment Analysis of Emergencies

摘要

With the rapid development of microblog, millions of Internet users share their opinions on different aspects of daily life. By analyzing and monitoring sentiment information extracting from tweets related to an important event, we are able to gain insights into variation trends of users' sentiment. In this paper, we focus on extracting public sentiment of microblog emergencies. A subtopic-level opinion mining method is proposed based on two-phase optimization. Different subtopics of emergencies are extracted based on retweets. Opinion tweets are classified to different subtopics. The sentiment score of opinion holders is calculated. The above results are optimized based on users and endorsement interactions between users. Experimental results validate the effectiveness of the proposed method.