Analysis of Twitter Users’ Mood for Prediction of Gold and Silver Prices in the Stock Market

Ch. 19. P. 190–197.

Porshnev Alexander, Redkin Ilya

The question about possibilities to use Twitter users’ moods to increase accuracy of stock price movement prediction draws attention of many researchers. In this paper we examine the possibility of analyzing Twitter users’ mood to improve accuracy of predictions for Gold and Silver stock market prices. We used a lexicon-based approach to categorize the mood of users expressed in Twitter posts and to analyze 755 million tweets downloaded from February 13, 2013 to September 29, 2013. As forecasting technique, we select Support Vector Machines (SVM), which have shown the best performance. Results of SVM application to prediction the stock market prices for Gold and Silver are discussed.

Keywords: общественные настроения, метод опорных векторов, золото, поведенческие финансы, mood, psychological states of internet users, twitter, предсказание, gold, prediction, Support Vector Machine, твиттер, психологическое состояние, silver, серебро, behavioral finance

In book

Analysis of Images, Social Networks and Texts

Vol. 436: 3rd International Conference on Analysis of Images, Social networks, and Texts. , NY: Springer, 2014.