sainithinkadarla / nlp_project

Text-based Chat Analysis

Description

This project analyzes text-based chat data to extract meaningful insights, including sentiment analysis, word frequency analysis, and topic modeling. The analysis is presented through various visualizations such as word clouds and sentiment trends over time.

Installation

Prerequisites

• Python 3.x
• Flask
• NLTK
• Pandas
• NumPy
• Seaborn
• Matplotlib
• Scikit-learn
• WordCloud

Steps

1. Clone the repository:

   git clone https://github.com/Sainithinkadarla/NLP_project.git

2. Navigate to the project directory:

   cd NLP_project

3. Install the required dependencies:

   pip install -r requirements.txt

Usage

1. Run the Flask app:

   python flask_app/app.py

2. Open a web browser and go to http://127.0.0.1:5050/.
3. Upload your chat file in the provided format and click "Analyze".

Project Structure

• app.py: The main Flask application script.
• templates/index.html: The homepage template.
• templates/results.html: The results page template.
• static/images/: Directory to store generated images such as word clouds and sentiment trends.

Technologies Used

• Python
• Flask
• NLTK
• Pandas
• NumPy
• Seaborn
• Matplotlib
• Scikit-learn
• WordCloud

Features

• Cleans and preprocesses chat data.
• Performs sentiment analysis using NLTK's VADER.
• Analyzes word frequencies and generates word clouds.
• Conducts topic modeling using LDA.
• Visualizes sentiment trends and message volumes over time.