SENTIMENT ANALYSIS - the expression of an emotion
The word sentiment is related to a term "Semantics" which is the branch that deals with linguistics and logic concerned with meaning. Sentiment is an attitude towards a thought, a mood, or judgment prompted by a feeling with a specific view or a notion. When such an emotion is refined sensibly with a categorized context which can help in understanding opinions of a person - then this process of interpretation is known as Sentimental Analysis.
Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral.Sentiment analysis helps data analysts within large enterprises gauge public opinion, conduct nuanced market research, monitor brand and product reputation, and understand customer experiences. This process, also known as “opinion mining,” is often used by companies and brands as a strategy for social media monitoring to manage large amounts of data and gain consumer insights to learn more about customers and competitors.
A sentiment analysis system for text analysis combines natural language processing (NLP) and machine learning techniques to assign weighted sentiment scores to the entities, topics, themes and categories within a sentence or phrase. In addition, data analytics companies often integrate third-party sentiment analysis APIs (Application Program Interface) into their own customer experience management, social media monitoring, or workforce analytics platform, in order to deliver useful insights to their own customers.
In other words, opinion mining and sentiment analysis mean an opportunity to explore the mindset of the audience members and study the state of the product from the opposite point of view. This makes sentiment analysis great tool for:
Expanded Product Analytics, Market Research , Reputation Management, Precision Targeting, Marketing Analysis, Public Relations (PR), Product Reviews, Net Promoter Scoring, Product Feedback, Customer Service.
Sentiment analysis is an incredibly valuable technology for businesses because it allows getting realistic feedback from your customers in an unbiased (or less biased) way. Done right, it can be a great value-added to your systems, apps, or web projects.
By Jaya Darshana S
Intern COE-AI lab