Publication | Closed Access
AI and Opinion Mining
189
Citations
9
References
2010
Year
Artificial IntelligenceEngineeringPublic OpinionCommunicationMultimodal Sentiment AnalysisSentiment AnalysisJournalismText MiningNatural Language ProcessingComputational Social ScienceSocial MediaData ScienceComputational LinguisticsAffective ComputingLanguage StudiesContent AnalysisSocial Medium MiningOpinion MiningKnowledge DiscoveryIntelligent AnalyticsSocial Media MiningSocial ComputingSocial Media ContentSocial Medium DataLinguisticsOpinion Aggregation
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.
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