Title :
Public Opinion Analysis of Microblog Content
Author :
Lu Yonghe ; Chen Jianhua
Author_Institution :
Sch. of Inf. Manage., Sun Yat-Sen Univ., GuangZhou, China
Abstract :
In this paper, a public opinion analysis system is built up. It consists of a crawler used to retrieve online microblog content and a text classifier for distinguishing sentimental content. This system is used to identify public opinions towards certain topics. Microblogs are divided into three categories based on their emotional tendency, namely "positive", "negative" and "objective", and then the microblogs are classified according to this categories. The classifier is constructed applying Support Vector Machine algorithm and the precision of classification exceeds 90%.
Keywords :
Web sites; content-based retrieval; pattern classification; support vector machines; text analysis; crawler; online microblog content retrieval; public opinion analysis system; public opinion identification; sentimental content; support vector machine algorithm; text classifier; Analytical models; Classification algorithms; Crawlers; Educational institutions; Sentiment analysis; Text categorization; Training;
Conference_Titel :
Information Science and Applications (ICISA), 2014 International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4799-4443-9
DOI :
10.1109/ICISA.2014.6847451
