Sentiment Analysis and Opinion Mining
- 23 May 2012
- journal article
- Published by Springer Science and Business Media LLC in Synthesis Lectures on Human Language Technologies
- Vol. 5 (1), 1-167
- https://doi.org/10.2200/s00416ed1v01y201204hlt016
Abstract
Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. For the first time in human history, we now have a huge volume of opinionated data recorded in digital form for analysis. Sentiment analysis systems are being applied in almost every business and social domain because opinions are central to almost all human activities and are key influencers of our behaviors. Our beliefs and perceptions of reality, and the...Keywords
This publication has 124 references indexed in Scilit:
- Lexicon-Based Methods for Sentiment AnalysisComputational Linguistics, 2011
- Adversarial Web SearchFoundations and Trends® in Information Retrieval, 2010
- On Lying and Being Lied To: A Linguistic Analysis of Deception in Computer-Mediated CommunicationDiscourse Processes, 2007
- Information ExtractionFoundations and Trends® in Databases, 2007
- Text mining for product attribute extractionACM SIGKDD Explorations Newsletter, 2006
- RECOGNIZING STRONG AND WEAK OPINION CLAUSESComputational Intelligence, 2006
- Lying Words: Predicting Deception from Linguistic StylesPersonality and Social Psychology Bulletin, 2003
- Conference reviewintelligence, 2000
- Authoritative sources in a hyperlinked environmentJournal of the ACM, 1999
- A tutorial on hidden Markov models and selected applications in speech recognitionProceedings of the IEEE, 1989