Opinion Mining (OM)

At the crossroads of Information Retrieval and of Computational Linguistics, the Opinion Mining (OM) exists. It is concerned with the analysis of the opinions expressed in documents. Opinion mining or sentiment analysis refers to the application of natural language processing, computational linguistics and text analysis to identify and extract subjective information in source materials.

OM aims to determine the attitude of a speaker with respect of some topic of a document. The attitude may be his judgement or evaluation, affective state, or the intended emotional communication. The basic task in OM is classify the polarity (positive vs. negative) of a given text at the document, sentence or feature/aspect level.

In this domain, the problem is that most OM algorithms rely on using simple terms to extract the sentiment about a product or service, whereas linguistic nuances and differing contexts make it extremely difficult to determine a text into a simple pro or con sentiment.

   ● www.wikipedia.org.

   ● Bing Liu 2010. Sentiment Analysis and Subjectivity. Handbook of Natural Language Processing. Second Edition

       (Ed. by Indukhya and Damerau).