Sentiment Analysis Using LSTM

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Author(s): Anweshan Mukherjee (St. Xavier's College (Autonomous), India), Rajarshi Saha (St. Xavier's College (Autonomous), India), Ashwin Gupta (St. Xavier's College (Autonomous), India), Debabrata Datta (St. Xavier's College (Autonomous), India)and Anal Acharya (St. Xavier's College (Autonomous), India)
Copyright: 2023
Pages: 24
Source title: Encyclopedia of Data Science and Machine Learning
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-7998-9220-5.ch057

Keywords: Data Analysis and Statistics / Information Science Reference / Knowledge Management and Library Science / Machine Learning

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Abstract

Sentiment analysis is a vast growing field as various branches of artificial intelligence are being used in different fields. Incorporating sentiment analysis in the field of psychology would be of great help to both doctors for easy diagnosis and patients for self-checking. The research work proposed in this article focuses on obtaining the dependency of one word with others in its current context using long short-term memory (LSTM) for obtaining the sentiment. The dataset used consists of 156060 movie reviews and a model was trained to classify the cleaned text data into three classes – Negative, Neutral, and Positive. The performance of the model was evaluated by checking the loss generated and the validation accuracy after each epoch. The model and its hyper parameters were also tuned to obtain the best model in terms of validation accuracy.

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