Sentiment Analysis (SA) aims to determine the attitude of a speaker or a writer with respect to some topic or the overall contextual polarity of a document. It aims to identify and extract subjective information in source materials.
Sentiment analysis (sometimes known as opinion mining or emotion AI) refers to the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. Sentiment analysis is widely applied to voice of the customer materials such as reviews and survey responses, online and social media, and healthcare materials for applications that range from marketing to customer service to clinical medicine.
Generally speaking, sentiment analysis aims to determine the attitude of a speaker, writer, or other subject with respect to some topic or the overall contextual polarity or emotional reaction to a document, interaction, or event. The attitude may be a judgment or evaluation (see appraisal theory), affective state (that is to say, the emotional state of the author or speaker), or the intended emotional communication (that is to say, the emotional effect intended by the author or interlocutor).
Sentiment analysis is the measurement of positive and negative language.
It is a way to evaluate written or spoken language to determine if the expression is favorable, unfavorable, or neutral, and to what degree.
Typical algorithm-based sentiment analysis tools can handle huge volumes of data (ex. customer feedback) consistently and accurately. When paired with text analytics, sentiment analysis can reveals the customer’s opinions on a range and variety of topics.
Sentiment analysis is a type of data mining that measures the inclination of people’s opinions through natural language processing (NLP), computational linguistics and text analysis, which are used to extract and analyze subjective information from the Web - mostly social media and similar sources. The analyzed data quantifies the general public's sentiments or reactions toward certain products, people or ideas and reveal the contextual polarity of the information.
Sentiment analysis is also known as opinion mining.