A Study of Opinion Mining of Twitter Data for Forecasting Stock Market Movements

Author(s): Bhushan Jalamkar and Dr. MM Bhonde

Abstract:

Income estimation is an important topic that has attracted the attention of finance researchers for many years. It involves the assumption that material information disclosed in the past has some predictive relationship with future stock performance. This study aims to help stock market investors determine the best time to buy or sell stocks based on information obtained from historical prices. The decision will be made according to the decision tree classifier, one of the data mining techniques. To develop the model, we use the CRISP-DM method on real historical data of three large companies listed on the Amman Stock Exchange (ASE).

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