Sentment analysis (SA) is said to determine the exactness of the underlying emotion in a context and text. SA which is also called Emotion AI is mostly regarded as a popular application of Natural Language Processing (NLP). Basic sentiment analysis, especially for commercial use, can be narrowed down to classification of sentences, paragraphs, and posts or documents as negative, neutral, or positive. A more complex processing of sentiment and attitude, extraction of meaning, classification of intent, and linguistics-based emotion analysis are also gaining traction.
In this project, we try to to the sentimetn analysis task on the Bromwell High Reviews dataset from IMDb. We apply a specific form of recursive neural networks, LSTM, which has the ability to capture long term dependencies.
This dataset contains more than 20,000 reviews and the labels are classified as negative or positive. To run, unzip the Bromwell High Reviews dataset and put the files in the same directory as SentimentAnalysis.py file.
SentimentAnalyzor is tested on Python version 3.69 and Keras 2.3.1. Use pip to install packages, separately.