This project is a web application for sentiment analysis built using Streamlit. Sentiment analysis, also known as opinion mining or emotion artificial intelligence, uses natural language processing (NLP), text analysis, computational linguistics, and biometrics to identify, extract, quantify, and study affective states and subjective information. The application analyzes digital text to determine if the emotional tone of the message is positive, negative, or neutral.
- User Input: Users can input text to be analyzed.
- Sentiment Analysis: The application uses NLTK's Sentiment Intensity Analyzer to compute the sentiment score.
- Real-time Analysis: The sentiment of the input text is displayed in real-time upon clicking the "Analyze Text" button.
- User-friendly Interface: Built using Streamlit, the application provides an intuitive and interactive user interface.
At the startup:
After Entering Input
- Businesses can use this tool to analyze customer feedback and reviews to gain insights into customer satisfaction and areas for improvement.
- Marketers and brand managers can monitor social media platforms to gauge public sentiment towards products, services, or events.
- Platforms can use sentiment analysis to filter and flag inappropriate or harmful content based on its emotional tone.
- Researchers can analyze sentiment trends in survey responses, forums, and blogs to understand public opinion on different topics.
- Sentiment analysis can help in analyzing patient feedback to improve healthcare services and patient experience.
For any questions or suggestions, please contact on LinkedIn: https://www.linkedin.com/in/siddiquizainab/