WhatsApp Whisperer

Description:

Project Description: WhatsApp Chat Analyzer | NLP | Python, NLTK, HuggingFace

The WhatsApp Chat Analyzer is an advanced project utilizing Natural Language Processing (NLP) techniques to extract meaningful insights from WhatsApp chat data. By leveraging Python along with powerful NLP libraries such as NLTK and HuggingFace, this project provides a comprehensive analysis of chat conversations, offering valuable metrics and classifications.

TechStack:

- Python: The primary programming language for data processing and analysis.
- NLTK (Natural Language Toolkit): Used for natural language processing tasks such as tokenization, stop-word removal, and sentiment analysis.
- HuggingFace: Employed for more advanced NLP models and sentiment analysis.
- StreamLit : For Deployment of the project

Chat Data Extraction: Collected WhatsApp chat data exported as text files from user devices. This raw data forms the basis for subsequent analysis.

Key Features:

1] User Activity Analysis:
- Most Active Users: Identified the users who sent the most messages within the chat group, providing insights into engagement levels.
- Monthly Messages: Analyzed the number of messages sent each month to understand trends and patterns in communication.

2] Message Frequency Analysis:
- Most Frequent Messages: Determined the most commonly sent messages or phrases, highlighting popular topics or repeated information.
- Total Messages: Calculated the total number of messages sent within the group and per user, offering a detailed view of participation.

3] Time Series Classification:
- Monthly Activity: Classified chat activity on a monthly basis to visualize long-term trends and seasonal variations.
- Daily Activity: Examined daily message patterns to identify peak usage times and daily communication habits.
- Weekly Activity

4] Sentiment Analysis:
- Sentiment Classification: Analyzed the sentiment of all messages using NLTK and HuggingFace models, categorizing them as positive, negative, or neutral.
- Sentiment Trends: Explored how sentiment changes over time, providing insights into the emotional tone of conversations.

The WhatsApp Chat Analyzer showcases the power of NLP and data analytics in transforming raw chat data into meaningful insights, providing a valuable tool for analyzing communication dynamics within chat groups.


Link : Streamlit (bhargavm123-nlp-whatsapp-chat-app-om0iur.streamlit.app)