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Sentiment analysis (also known as opinion mining or emotion AI) is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information.
Multimodal sentiment analysis is a technology for traditional text-based sentiment analysis, which includes modalities such as audio and visual data. [1] It can be bimodal, which includes different combinations of two modalities, or trimodal, which incorporates three modalities. [ 2 ]
In 2017-18, in independent surveys published in leading journals including in Elsevier's Information Processing Management journal, Prof Amir Hussain and his collaborator (and former PhD student), Dr Erik Cambria, were ranked as the world's top two most productive/influential [9] researchers in the field of Sentiment Analysis (since 2000).
He is best known for his research on sentiment analysis (also called opinion mining), fake/deceptive opinion detection, and using association rules for prediction. He also made important contributions to learning from positive and unlabeled examples (or PU learning ), Web data extraction, and interestingness in data mining.
The application of sophisticated linguistic analysis to news and social media has grown from an area of research to mature product solutions since 2007. News analytics and news sentiment calculations are now routinely used by both buy-side and sell-side in alpha generation, trading execution, risk management, and market surveillance and compliance.
Hutto, Clayton J., and Eric Gilbert. "Vader: A parsimonious rule-based model for sentiment analysis of social media text." Eighth international AAAI conference on weblogs and social media. 2014. Gilbert, Eric, and Karrie Karahalios. "Predicting tie strength with social media."
He has published more than 350 research papers covering all major areas of NLP in top journals and conferences and has guided more than 300 students for their PhD, masters and undergraduate research. Automatic Sarcasm Detection, Multilingual Computation, Indian Language Neural Machine Translation and Indowordnet are some of his research trail ...
Reviewed by Maik Stührenberg. This paper [1] is thoroughly structured and combines the theory of web genres with dialogue theory to examine Wikipedia talk pages. Since Wikipedia is a web genre, "Wikicussions" (as the authors call them) form a subgenre.