Stock Market Prediction Using Microblogging Sentiment Analysis and Machine Learning

Paraskevas Koukaras · Christina Nousi · Christos Tjortjis

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Stock Market Forecasting Methods Financial Markets and Investment Strategies Sentiment Analysis and Opinion Mining

Abstract

The use of Machine Learning (ML) and Sentiment Analysis (SA) on data from microblogging sites has become a popular method for stock market prediction. In this work, we developed a model for predicting stock movement utilizing SA on Twitter and StockTwits data. Stock movement and sentiment data were used to evaluate this approach and validate it on Microsoft stock. We gathered tweets from Twitter and StockTwits, as well as financial data from Finance Yahoo. SA was applied to tweets, and seven ML classification models were implemented: K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Logistic Regression (LR), Naïve Bayes (NB), Decision Tree (DT), Random Forest (RF) and Multilayer Perceptron (MLP). The main novelty of this work is that it integrates multiple SA and ML methods, emphasizing the retrieval of extra features from social media (i.e., public sentiment), for improving stock prediction accuracy. The best results were obtained when tweets were analyzed using Valence Aware Dictionary and sEntiment Reasoner (VADER) and SVM. The top F-score was 76.3%, while the top Area Under Curve (AUC) value was 67%.

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References

2016Sentiment analysis of Twitter data for predicting stock market movements 2020Predicting Stock Market Trends Using Machine Learning and Deep Learning Algorithms Via Continuous and Binary Data; a Comparative Analysis 2016The impact of microblogging data for stock market prediction: Using Twitter to predict returns, volatility, trading volume and survey sentiment indices 2016Stock market index prediction using artificial neural network 1987THE PARETO PRINCIPLE: ITS USE AND ABUSE 2017Predicting Stock Market Behavior using Data Mining Technique and News Sentiment Analysis 2021S_I_LSTM: stock price prediction based on multiple data sources and sentiment analysis 2018The Interaction between Microblog Sentiment and Stock Returns: An Empirical Examination1

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