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Comparative analysis of Stock Market Prediction Algorithms based on Twitter Data
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 174 - Number 29 |
| Year of Publication: 2021 |
| Authors: R. Sai Venkata Ramana, M. Reddy Durga Sree, Ramakrishna Gandi, A. Sankar Reddy |
10.5120/ijca2021921214
|
R. Sai Venkata Ramana, M. Reddy Durga Sree, Ramakrishna Gandi, A. Sankar Reddy . Comparative analysis of Stock Market Prediction Algorithms based on Twitter Data. International Journal of Computer Applications. 174, 29 ( Apr 2021), 22-26. DOI=10.5120/ijca2021921214
Abstract
Stock market prediction is considered as one of the most promising research area that is attainning the attention of various researchers. The vital information which is available for access is assumed to have predictive relationships to the future stock returns. The present work gives information to the investors so that the decision could be made better during the purchase of stocks. The factors that contribute towards the decision are the historical prices of stocks and tweet comments regarding the same. The proposed method uses four methods for predicting the stock market status, namely, Linear Regression (LR), Support Vector Machine (SVM), Naïve Bayes (NB), and Random Forest (RF) approaches. When evaluated with standard datasets, experimental results concluded that the SVM based prediction has significant predicting performance than the other methods. The proposed work gives a comparison of factors in order to decide the purchase.
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