Development and Evaluation of a Google Chrome Extension for Real-Time Emotion Detection in Web Text Using Machine Learning and Natural Language Processing

This research paper introduces a novel approach that leverages machine learning and natural language processing (NLP) techniques to detect emotions in text. The proposed system includes a Google Chrome extension that allows users to swiftly and effortlessly evaluate the emotional content of the websites they visit. It employs various NLP methods, such as keyword extraction and tokenization, to extract relevant features from the text. These features are then used to train a machine learning model capable of accurately predicting the emotional content of new text. The system demonstrates high accuracy on multiple benchmark datasets, showcasing its effectiveness in real-world applications.