Sentiment Analysis from Text Using LSTM

The classification of emotional states from poetry or formal text has received less attention by the experts of computational intelligence in recent times as compared to informal textual content like SMS, email, chat, and online user reviews. In this study, an emotional state classification system for text is proposed using the latest and cutting edge technology of Artificial Intelligence, called Deep Learning. For this purpose, an attention-based LSTM model is implemented on the text corpus. The proposed approach classifies the text into different emotional states, like neutral, joy, fear, sadness, anger, etc.

Keywords: Deep learning, emotion recognition, text, attention-based LSTM, formal text, emotional states