Lexicon-based Comments-oriented News Sentiment Analyzer system
Expert Systems with Applications: An International Journal
Analyzing Online Review Helpfulness Using a Regressional ReliefF-Enhanced Text Mining Method
ACM Transactions on Management Information Systems (TMIS)
Review summarization based on linguistic knowledge
DASFAA'12 Proceedings of the 17th international conference on Database Systems for Advanced Applications
Identifying the semantic orientation of terms using S-HAL for sentiment analysis
Knowledge-Based Systems
Sentimental Spidering: Leveraging Opinion Information in Focused Crawlers
ACM Transactions on Information Systems (TOIS)
Business Intelligence and Analytics: Research Directions
ACM Transactions on Management Information Systems (TMIS)
Mining Divergent Opinion Trust Networks through Latent Dirichlet Allocation
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Data intensive review mining for sentiment classification across heterogeneous domains
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
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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. This Trends & Controversies department and the next include three articles on opinion mining from distinguished experts in computer science and information systems. Each article presents a unique innovative research framework, computational methods, and selected results and examples.