Topic Modeling on Customer Reviews using Advanced NLP Techniques

This project involves performing topic modeling on customer reviews to uncover hidden themes and patterns within the text data. By applying advanced Natural Language Processing (NLP) techniques, we can identify key topics and trends that help in understanding customer sentiments and improving business strategies.

Features

• Extracts and analyzes topics from a large corpus of customer reviews.
• Uses techniques such as Latent Dirichlet Allocation (LDA) for topic modeling.
• Visualizes topics and their distribution across the reviews.
• Provides insights into common themes and customer sentiments.

Installation

To set up the topic modeling system on your local machine, follow these steps:

1. Clone the Repository

   git clone https://github.com/username/topic-modeling-customer-reviews.git
   cd topic-modeling-customer-reviews

2. Set Up Virtual Environment (Optional but Recommended)

   python3 -m venv venv
   source venv/bin/activate   # On Windows: venv\Scripts\activate

3. Install Required Packages

   pip install -r requirements.txt

Usage

To start the topic modeling analysis, run the main script with your dataset:

python topic_modeling.py --input