

There has been a lot of advancements in the field of Artificial Intelligence and has changed the ways we use computers. From last few decades, AI has become good at reading emotional reactions of humans. They were able to detect the emotions in a text through keystroke attributes related with emotions like (fear, anger, disgust, shame, guilt, joy, sadness). The reading emotion is a lot different from the understanding of emotions. Now, a student has finally designed an AI system which will detect emotions in emails and texts. It could have the option for detecting content that shows help and even suicidal intention. It is easy to detect emotions in voice messages through voice inflexion and tone. However, detecting emotion through emails or texts can be a difficult task even when you a user is using smiley faces of exclamation points.

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Eden Saig a mastermind behind this idea, presented his project in "Sentiment Classification of Texts in Social Networks". It has developed this system of detecting emotions in texts. For better use of the system, we should understand its design and fire out how we can make use of it completely. He made a system that records the repeated word patterns. Sentiment analysis is also known as opinion mining is the hottest topic of 2017 as it analysis sentiments. It will be highly beneficial as you would know what user thinks about your product, whether they like it or not. The computer will detect the language and will tell you if it is positive, neutral or negative. The Sentiments are analysed using, lexicon-based model, though there are many other ways of analysing sentiments.

Big data and artificial intelligence systems have been helping in improving the better user experience. The most important use of sentiment analysis is in product marketing. It finds out which feature is not working out by analysing the negative emotions.

