DocumentCode
1505555
Title
AI and Opinion Mining
Author
Chen, Hsinchun ; Zimbra, David
Volume
25
Issue
3
fYear
2010
Firstpage
74
Lastpage
80
Abstract
The advent of Web 2.0 and social media content has stirred much excitement and created abundant opportunities for understanding the opinions of the general public and consumers toward social events, political movements, company strategies, marketing campaigns, and product preferences. Many new and exciting social, geopolitical, and business-related research questions can be answered by analyzing the thousands, even millions, of comments and responses expressed in various blogs (such as the blogosphere), forums (such as Yahoo Forums), social media and social network sites (including YouTube, Facebook, and Flikr), virtual worlds (such as Second Life), and tweets (Twitter). Opinion mining, a subdiscipline within data mining and computational linguistics, refers to the computational techniques for extracting, classifying, understanding, and assessing the opinions expressed in various online news sources, social media comments, and other user-generated content. Sentiment analysis is often used in opinion mining to identify sentiment, affect, subjectivity, and other emotional states in online text.
Keywords
computational linguistics; data mining; social networking (online); Al; Facebook; Flikr; Web 2.0; Yahoo forums; YouTube; blogosphere; blogs; business related research questions; computational linguistics; data mining; opinion mining; social media content; social network sites; Artificial intelligence; Blogs; Companies; Computational linguistics; Data mining; Facebook; Second Life; Social network services; Twitter; YouTube; Wal-Mart; Web 2.0; intelligent systems; opinion mining; sentiment analysis;
fLanguage
English
Journal_Title
Intelligent Systems, IEEE
Publisher
ieee
ISSN
1541-1672
Type
jour
DOI
10.1109/MIS.2010.75
Filename
5475086
Link To Document