The week's pick
Reseach Article
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.
References
- Qasem a. Al-radaideh, Adel Abu Assaf, Eman Alnagi, “Predicting Stock Prices using Data Mining Techniques”, The International Arab Conference on Information Technology (ACIT’2013)
- Nirbhey Singh Pahwa, Neeha Khalfay, Vidhi Soni, Deepali Vora,” Stock Prediction using Machine Learning a Review Paper” International Journal of Computer Applications (0975 – 8887) Volume 163 – No 5, April 2017.
- Mustansar Ali Ghazanfar, Saad Ali Alahmari, Yasmeen Fahad Aldhafiri, Anam Mustaqeem, Muazzam Maqsood, and Muhammad Awais Azam, “Using Machine Learning Classifiers to Predict Stock Exchange Index”, International Journal of Machine Learning and Computing, Vol. 7, No. 2, April 2017
- Osman Hegazy, Omar S. Soliman and Mustafa Abdul Salam, A Machine Learning Model for Stock Market Prediction, International Journal of Computer Science and Telecommunications Volume 4, Issue 12, December 2013.
- Zahid Iqbal, R. Ilyas, W. Shahzad, Z. Mahmood and J. Anjum, “Efficient Machine Learning Techniques for Stock Market Prediction”, Int. Journal of Engineering Research and Applications, Vol. 3, Issue 6, Nov-Dec 2013, pp.855-867
- Saahil Madge Predicting Stock Price Direction using Support Vector Machines
- Shubham Jain, Mark Kain, “Prediction for Stock Marketing Using Machine Learning”, International Journal on Recent and Innovation Trends in Computing and Communication Volume: 6 Issue: 4
- Robert Chun, Thomas Austin, “STOCK PRICE PREDICTION USING DEEP LEARNING”, https://scholarworks.sjsu.edu/cgi/viewcontent.cgi? referer=https://www.google.com/ &httpsredir=1&article=1639&context=etd_projects
- Nishanth C P , Dr. V K Gopal , Vinayakumar R , Lakshmi Nambiar , Dileep G Menon, “Predicting Market Prices Using Deep Learning Techniques”, International Journal of Pure and Applied Mathematics Volume 118 No. 20 2018, 217-223.
- Eunsuk Chong , Chulwoo Han , and Frank C. Park,” Deep Learning Networks for Stock Market Analysis and Prediction: Methodology, Data Representations, and Case Studies” Article in Expert Systems with Applications · April 2017.
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