Movie Reviews Sentiment Analysis

This is a movie sentiment analysis project that we will use the IMDB dataset to train our machine learning models. Then, we use these models to classify whether a movie review is positive or negative.

Authors

Lim Chia Chung @Jacky0111
Lim Ming Jun @mingjun1120
Leong Yit Wee @leongyitwee

Python Version

Python 3.8

Application Used

Google Colab

Documentation

Model Training (DistilBert): Ktrain
Crawling Data: request-html

How to run

Open the NLP Assignment folder in Google Colab. Then, follow these steps:

Run the 2_preprocess_data.ipynb
Run DistilBERT.ipynb inside Lim Ming Jun folder
Run Long_Short-Term_Memory(LSTM).ipynb inside Lim Chia Chung folder
Run Convolutional Neural Network Tutorial (CNN).ipynb inside Leong Yit Wee folder
Run Local Sentiment Analysis App.ipynb

Web Scraping

For this part, go to the MovieScraper folder first and the run the main.py (scraper). The output will store as scrap_movie_reviews.csv.

How this program works:

Basically, we use the IMDB dataset to train on the DistilBert, LSTM and CNN models. Then, we will compare the performance of these 3 models via Local Sentiment Analysis App.ipynb where this notebook can do a single review analysis input by users as well as multiple reviews analysis by feeding the data that we have scraped through main.py in MovieScraper folder.

Note:

The scraped data are well labeled with POSITIVE and NEGATIVE sentiment.

Jacky0111/Movie-Reviews-Sentiment-Analysis