StockTwits MCP (keyless public read).
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Updated
Aug 26, 2026 - TypeScript
StockTwits MCP (keyless public read).
Detecting the GameStop Crash using NLP
Check for Stocks Social Mentions
Project to display StockTwits tweets from API call and search from user. (Under construction, does not work)
FinTwit-Bot is a Discord bot designed to track and analyze financial markets by pulling data from platforms like Twitter, Reddit, and Binance. It features customizable tools for sentiment analysis, market trends, and portfolio tracking to help traders stay informed and make data-driven decisions.
Real-time stock sentiment analysis using Reddit, StockTwits and FinBERT
Free momentum + social sentiment scanner for OpenClaw. S&P 500 + Nasdaq 100 + crypto. Zero API cost.
[EE7207]NEURAL NETWORKS & DEEP LEARNING Project:ModernBERT-base fine-tuning (SFT) pipeline for 3-class cryptocurrency sentiment analysis on StockTwits data, built for Slurm-managed HPC clusters.
Stocktwits ticker news monitoring
An unofficial, modern, very much work-in-progress client for StockTwits APIs.
One million StockTwits messages collected via API and stored in MongoDB, preprocessed with emoji/punctuation preservation, and classified using TF-IDF with Logistic Regression, SVM, Naïve Bayes, Random Forest, and MLP; extended with n-gram analysis, forecasting regressions, and event-study tests linking sentiment to short-term stock returns
A sentiment-driven trading algorithm using deep learning to analyze social media sentiment from StockTwits, Twitter, and Reddit for stock market predictions. Built with Python, TensorFlow/Keras, and MySQL.
Fetch Jerome Powell speeches feed from federalreserve.org RSS and post to StockTwits
Frontend Engineer Takehome Project built with ReactJS & Serverless Functions
Determines the sentiment (bullish, bearish) of stocks on a watchlist using Twitter tweets
Sentiment analysis tool for Stocktwits.
Fast and multi threaded stock data scraper written in Java using HTMLUnit and minimal-json. Scrapes Finviz and Stocktwits for data, and stores the information in a csv file.
Applied random forests to classify sentiment of over 1M cryptocurrency-related messages on StockTwits posted between 28/11/2014 and 25/07/2020
Source codes to scrape tweets from the Stocktwits API and store as JSON. Preprocessing steps for NLP classification.
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