The process of sentiment analysis is used to determine the attitude of a speaker or a writer with respect to some topic or the overall contextual polarity of a document. The attitude may be a judgment or opinion, expressed in a verbal or written form.
Opinion mining (sometimes referred to as sentiment analysis 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.
The first use of the term "sentiment analysis" can be traced back to the 1950s. In the early days of computational linguistics, researchers were interested in using computers to automatically analyze text to extract objective information, such as who did what to whom.
However, it wasn't until the early 2000s that sentiment analysis really took off, with the rise of online customer reviews and social media.
There are a few different techniques that can be used for sentiment analysis, but the most common one is lexical analysis.
Lexical analysis is a way of analyzing text by looking at the words that are used. This can be done using a dictionary, which is a list of words and their meanings.
For each word in the text, the sentiment score is calculated. The score is based on the dictionary definition of the word. If a word has a positive sentiment, the score is increased. If a word has a negative sentiment, the score is decreased.
The final sentiment score is the sum of all the individual scores.
Sentiment analysis can be used for a variety of different applications, such as:
Customer service: Sentiment analysis can be used to automatically analyze customer feedback and identify areas that need improvement.
Marketing: Sentiment analysis can be used to understand how customers feel about a product or service, and to identify areas that need improvement.
Political analysis: Sentiment analysis can be used to understand public opinion on a particular issue.
Product reviews: Sentiment analysis can be used to automatically analyze product reviews and identify areas that need improvement.