Contextual Emotion Detection in Text using Deep Learning and Big Data

Conversations on social media nowadays generate a large amount of text, which is a form of emotion. Users respond emotionally to users by communicating through text messages on various social media or other media. This work demonstrates gathering learning to identify emotions present in a sentence of messages. Printed speeches are given relevant feeling discover in our model from user text automatically such as Happy, Sad, Angry and Wow etc. When a user expresses their feelings through text, our model automatically identifies the user's feelings and sets up key related emoji like Happy, Sad, Angry, Great, etc. The LSTM model, Naive Bayes as well as SVM classifiers have been used to detect emotions.