Movie Sentiment Analysis

Descripton

Movie Sentiment Analysis is a Natural Language Processing project, which categorizes the movie reviews as Positive and Negative using various techniques and tools of Natural Language Processing, which includes text preprocessing, machine learning, and visualization, along with an interactive platform to predict the sentiment of a given input text by users.

Features

Text Cleaning & Preprocessing

• Noise removal from text data

• Normalizes and tokenizes text

• Applying stop word removal and text normalization

Data Visualization

• Visualizes sentiment distribution

• Presents word frequency patterns

• Assists in understanding the nature of the dataset

Machine Learning Models

• Implements four different ML models for sentiment classification
• Compares model performance

Model Evaluation

• Utilises evaluation metrics such as:

• Accuracy

• F1-S

• Performance comparison between models

Interactive Application

• Streamlit-Based UI
• Allows users to input custom text
• Makes predictions in real time \Gamma

Technologies Used

• Programming Language: Python

• Libraries & Tools:

• Pandas

• NumPY

• Matplotlib

• Scikit-learn

• NLTK

• Streamlit

• Installation

Clone

git clone https://github.com/16A9DA/Movie-Sentiment