Product overview
MonkeeMath is a web-based tool that helps investors by applying AI-driven sentiment analysis to online conversations about stocks. It collects public comments, evaluates whether the tone of discussion leans positive or negative, and visualizes the results so users can factor sentiment into their decision-making.
How opinions are gathered and interpreted
- The application pulls stock-related posts and comments from social platforms such as Reddit and Stocktwits.
- It uses an AI engine (ChatGPT) to read those messages and determine whether each contribution expresses optimism or pessimism about a given ticker.
- Analysis focuses on recent chatter, with movement likelihood estimates derived from the previous day’s commentary.
Visual reports and probability metrics
MonkeeMath turns sentiment results into charts and tables that are easy to scan. For each tracked symbol the app calculates and displays a percentage score indicating the probability of a short-term move based on the prior day’s aggregated sentiments.
Interactive prediction experience
Users can register profiles, submit their own short-term stock predictions, and participate in a prediction mini-game. Accuracy is tracked and contributors are ranked on a leaderboard, creating a competitive layer for testing forecasting skill.
Main dashboard sections
- Prediction feed — a real-time stream of user forecasts and outcomes.
- Movement charts — graphical representations of sentiment trends and implied probabilities.
- Advanced analysis — deeper data tools and tables for users who want to drill into the underlying signals.
Extra tools and alternatives
A lightweight alternative noted in the original copy is DrugCard Simple Search (free), which may serve different use cases; MonkeeMath remains focused on sentiment-driven investment signals.
Who benefits from MonkeeMath
The platform is geared toward investors and traders who want a supplementary data stream derived from social conversation. It’s intended as a decision-support tool to be used alongside traditional research and risk management practices.
Technical
- Web App
- Full