Social media is flooded with data that is generated by bloggers, committee, business, health, marketing, education, etc., in large amount. Extracting the data information from various fields like social media, marketing, reviews, conference publications and advertisement is done to perform sentiment analysis. These text data have some emotions hidden in it, and data analysing is carried out by natural language processing (NLP). NLP is application of artificial intelligence that help machine to read text by simulating the human capability to know language. Sentiment analysis is type of data mining that measures the opinion of the users or the customer or the blogger through the natural language processing, which can be utilized to extricate and dissect emotional data from web for the most part web based life. The main purpose of sentiment analysis is to classify emotions into positive, negative and neutral. The applications of sentiment analysis are in the financial market, area of reviews of consumer services and products to monitor customer sentiment and catch the trending topics. Sentiment analysis has challenges like multilingual sentiment analysis, emotion detection, and data sparsity from the different data by social media, marketing, emails, advertisement, movie review etc.

Sentiment analysis, natural language processing, artificial intelligence

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