| Autor: |
Tirthank Shah, Chetan Gondaliya, Ajay M. Patel |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
IOP Conference Series: Materials Science and Engineering |
| ISSN: |
1757-899X |
| DOI: |
10.1088/1757-899x/1020/1/012023 |
| Popis: |
Outbreak and spread of the Covid-19 pandemic have touched to the core of our sentiments Indian stock market has seen a roller coaster ride so far this year amid the Covid-19 pandemic Sentiments have turned out to be a significant influence on the movement of the Indian stock market and pandemic has only added more steam This study with the limelight on the Covid-19 pandemic is an endeavour to investigate the classification accuracy of selected ML algorithms under natural language processing for sentiment analysis and prediction for the Indian stock market The study proposes the framework for sentiment analysis and prediction for the Indian stock market where six ML algorithms are put to test Consequently, the study highlights the superior algorithms based on accuracy results These superior algorithms can be potent input to build robust prediction models as a logical next step © Content from this work may be used under the terms of the Creative Commons Attribution 3 0 licence Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI Published under licence by IOP Publishing Ltd |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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