emoji-analysis

🧠 Multi-agent AI platform that extracts feature-level sentiment, detects emerging complaint trends, and surfaces prioritized recommendations from customer reviews. LangGraph + LLaMA 3.1 + React.

A Python tool that analyzes WhatsApp chat exports to generate detailed statistics about messages, media usage, and temporal patterns. Features include message counts, media stats, call analysis, and most used words/emojis.

Emoji-aware transformer model for five-class mental health detection from social media text.

Emoji-aware hate speech detection on Olympics Twitter data using GloVe embeddings, N-Grams, LSTM, Bi-LSTM, DBSCAN clustering, and Attention Mechanisms.

In-depth analysis of YouTube Data

AI-powered Regret-o-Meter: Paste your chaos, get your regret score, top regrets, and sarcastic roast. Pure fun, not serious.

This repository provides a comprehensive analysis of YouTube comments and related data, leveraging sentiment analysis, emoji usage, word cloud generation, and various graphical visualizations. Key steps include: Data Preparation, Sentiment, WordCloud, Emoji, Data Collection & Analysis

WhatsApp Chat Analyzer extracts insights from chat data, visualizing activity trends, emoji usage, and sentiment analysis using "ganeshkharad/gk-hinglish-sentiment". Built with Streamlit, Pandas, and Matplotlib for interactive analysis. 🚀

A Python-based tool that analyzes emojis to predict their associated emotions—positive, neutral, or negative—with clear confidence scores. It features both a simple console interface and an interactive Streamlit web app for real-time emoji sentiment analysis and exploration.