Sentiment Meets Stocks

Analyzing r/WallStreetBets discussions to predict tech stock movements using advanced NLP and time series forecasting

AAPL +2.4%
META +1.8%
MSFT -0.6%

About the Project

Bridging social media sentiment with stock market predictions

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Data Collection

Scraping real-time discussions from r/WallStreetBets using RedditExtractoR to capture retail investor sentiment

🧠

NLP Analysis

Custom finance lexicons with WSB-specific terms like "moon," "tendies," and "bullish" for accurate sentiment scoring

📊

Stock Prediction

ARIMA time series forecasting to predict stock price movements and correlate with sentiment trends

Research Problem

Does investor sentiment on WallStreetBets influence long-term stock prices?

Tech Stocks Analyzed

10 leading technology companies under the microscope

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Apple

AAPL
📘

Meta

META
📦

Amazon

AMZN
🏛

IBM

IBM
🏢

Microsoft

MSFT
🔍

Google

GOOG
🖥

Dell

DELL
🖨

HP

HPQ
🚖

Uber

UBER
🎨

Adobe

ADBE

Key Features

🎯 Sentiment Scoring

AFFIN & JOCKER lexicons enhanced with 45+ WSB-specific financial terms

📈 Time Series Forecasting

ARIMA models with automatic parameter selection and Box-Cox transformation

💹 Options Analysis

Tracking puts vs calls mentions to gauge market sentiment direction

🔄 Real-Time Data

Continuous scraping from Reddit and Yahoo Finance APIs

Results & Insights

Neutral Sentiment Dominance

Most discussions showed balanced sentiment, indicating equal buyer-seller influence across the board

📊

Sentiment Correlation

Clear correlation observed between sentiment scores and stock price trends over time

🎯

ARIMA Superiority

ARIMA models outperformed other forecasting methods for 9 out of 10 stocks analyzed

🚀

Uber Exception

Drift model proved more accurate for UBER, suggesting different market dynamics

Technology Stack

R
Python
RedditExtractoR
yfinance
tidytext
forecast
ggplot2
ARIMA

Ready to Explore?

Dive into the code, check out the analysis, or contribute to the project