Sentiment AI

How to know, what the world think about a particular stock, commodity or even a celebrity? Introducing Sentiment AI, it is designed to automate the process of gathering, analyzing, and summarizing online content related to any specified topic. It leverages web scraping and natural language processing (NLP) to scan the top relevant articles on a given topic from Google search results, providing users with insights into the sentiment and key takeaways of each article. Key Features: Web Scraping and Article Retrieval: The application automatically queries Google for the most relevant articles on a specified topic. It scrapes the top-ranked articles, fetching the title, body text, publication date, and other metadata for further analysis. Sentiment Analysis: Using NLP techniques, the AI model performs sentiment analysis on each article, determining whether the tone of the content is positive, neutral, or negative. The sentiment score is assigned on a scale from -10 to +10: A score of +10 indicates highly positive sentiment. A score of -10 indicates highly negative sentiment. A score of 0 indicates a neutral or balanced sentiment. Article Summarization: The application condenses long articles into concise summaries, providing users with the main points and key insights without the need to read the full article. The summary includes the tone and sentiment score, helping users quickly grasp the overall message and stance of the article.