Website Sentiment Analysis App 🎭💬

A Streamlit-based web app to predict emotions in text using a pre-trained machine learning model. The app supports two input modes:

1. Manual Text Input ✍️: Enter text directly to analyze its emotional tone.
2. Web Scraping 🌐: Provide a URL to scrape text from the web, preprocess it, and predict the emotions.

Features 🚀:

• Predicts emotions like anger 😠, joy 😂, sadness 😔, and more with emoji representation.
• Displays prediction probabilities 📊 using an interactive bar chart.
• Simple, user-friendly interface for both manual and web-based input.

Machine Learning Algorithms 🤖:

The app leverages multiple ML models for accurate emotion detection:

• Support Vector Classifier (SVC) 📈: Ensures robust separation of text classes.
• Logistic Regression 🧠: Ideal for interpreting probabilities and classifying emotions.
• Random Forest Classifier 🌲: Combines multiple decision trees for better accuracy and generalization.

Tech Stack 🛠️:

• Streamlit for the frontend.
• Scikit-learn for the pre-trained emotion detection model.
• BeautifulSoup for web scraping.
• Altair for data visualization.

Run and detect emotions in any text instantly! ✨💡

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Installation Instructions 📥

Clone this repository: git clone https://github.com/yourusername/TextEmotionDetectionApp.git cd TextEmotionDetectionApp

Install the required dependencies just if in case : !pip install pandas

!pip install numpy

!pip install BS4

!pip install streamlit

!pip install joblib

!pip install scikit-learn

!pip install altair

Run the app: streamlit run app.py

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Contributing 🤝