WhatsApp chats and sentiment analyzer, using Streamlit and Heroku deployment

Chat Love Predictor is a browser-based WhatsApp analyzer using the Love Theorem. It processes chats locally for privacy and shows insights like sentiment, reply speed, and interaction patterns. Try it:

WhatsApp Chat Analyzer is a Python-based tool that processes WhatsApp chat exports to provide detailed insights and visualizations of messaging patterns. Key features include user activity statistics, monthly and daily trends, emoji analysis, and sentiment evaluation, enabling users to explore their communication habits effectively.

WhatsApp chat analyzer is a data analysis project that involves natural language processing techniques to extract insights from WhatsApp chat history data. Specifically, it involves extracting, preprocessing, and analyzing the chat history data using NLP techniques to perform tasks such as sentiment analysis, named entity recognition, topic modelin

The WhatsApp Chat Analyzer web app is a PyCharm Python project that allows users to upload their WhatsApp chat history and perform various analyses on the data. The app provides a user-friendly interface and offers a range of features. It now also includes modules for sentiment analysis, keyword search, and message length analysis.

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we are taking the WhatsApp chat and analyzing the chat with the python using NLTK technique. We are concluding that whether the chat is which state

A machine learning project which will analyze whatsapp chat and tell the message type of each user like positive or negetive or neutral.

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Complete chat analysis of private as well as of public group chat with features like most active user, daily monthly and emoji analysis,

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The live webapp is hosted on render.

It is a WhatsApp Chat Analyzer which find sentiment of chats.

"WhatsApp Chat Analyzer: Python-based ML project for extracting insights & sentiment analysis from WhatsApp conversations. Explore data-driven insights!"

WhatsApp Chat Analyzer - Web App 📊 Analyze WhatsApp chat exports with sentiment analysis, word clouds, and activity insights. Built with Python, Streamlit, Pandas, and Plotly. 👥 Created by: GROUP 36 (SIC)

WhatsApp Chat Analyzer is a Streamlit web application designed to analyze and visualize WhatsApp chat data. This application provides various statistics, sentiment analysis, timelines, and visualizations to gain insights into your chat history.

The WhatsApp Chat Analyzer project aims to extract meaningful insights and patterns from WhatsApp chat data using Python. The analysis focuses on understanding communication behaviors, sentiment trends, and key discussion topics within the chat.

Streamlit WhatsApp Analyzer: upload exported chats, index them with FAISS embeddings, and explore activity, sentiment, topics, plus a Mistral-powered RAG Q&A that cites original messages.

The WhatsApp Chat Analyzer is a project that leverages machine learning and natural language processing techniques to analyze chat data from WhatsApp conversations. It provides insights such as message statistics, sentiment analysis, word clouds, and more.

A WhatsApp Chat Analyzer is a tool designed to extract insights from WhatsApp chat data. It analyzes message count, user activity, word frequency, sentiment, and media sharing patterns. Users can understand communication dynamics, identify trends, and gain insights into the content of their WhatsApp conversations.

The Whatsapp Chat Analyzer is a Python-based tool designed to analyze chat data exported from WhatsApp. It provides insights into various aspects of the chat, including statistics, timelines, activity patterns, sentiment analysis, word clouds, and emoji usage.

The WhatsApp Chat Analyzer is a powerful tool for analyzing and visualizing WhatsApp chat exports. It offers insights into message activity, user engagement, sentiment analysis, emoji usage, and frequent words. The app generates interactive charts, timelines, and heatmaps to help you better understand chat dynamics, with features like sentiment dis

WhatsApp Chat Analyzer: This Streamlit web app analyzes uploaded WhatsApp chat data, providing insights into message frequency, sentiment, and key word usage. Users can explore statistics for individual users and the overall group chat, making it easy to understand communication patterns and trends.

This Streamlit-based WhatsApp Chat Analyzer extracts insights from chat exports. It includes statistics, timelines, emoji and sentiment analysis, language detection, word clouds, and activity heatmaps. Users can view overall or individual chat behaviors interactively.

Chat Analyzer for whatsapp which analyses both, one to one chat and the chat in the group at various level, it also gives the sentiment of the chat. The app is also deployed on Heroku platform.

This repository houses a robust WhatsApp Chat Analyzer designed to extract meaningful insights from your chat data. Whether you're curious about group dynamics, interested in sentiment trends, or want to discover the core themes of your conversations, this tool has you covered.

WhatsApp Chat Analyzer is a robust tool for analyzing chats, detecting security threats, and automating sentiment analysis. It provides insights through data visualization dashboards using Matplotlib and Pandas, improving reporting accuracy and efficiency. The project enhances chat analysis with graphical reports and automated processes.