Skip to main content

Performance Analysis of Indian Stock Market via Sentiment Analysis and Historical Data

  • Conference paper
  • First Online:
Data Science and Intelligent Applications

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 52))

  • 1570 Accesses

Abstract

Stock market has always generated interest among the people since the time of its initiation. It is a very complex and challenging system, where people invest to gain money in order to attain higher gains. But the scenario may be negative if the investment is made in the stocks without any proper analysis. The performance of any stock depends on many parameters and factors like historical prices, social media data, news, country economics, production of the company, etc. In our research, we consider two major factors like historical prices and social media data and will let the investors give an idea about the stock performance in the nearby future. Therefore, we combine the sentiments of the different stakeholders across the Internet with historic prices of the stock to predict the stock recital. For combining the above approaches, we are using the decision tree approach of machine learning for classification and prediction for more accurate prophecy. The proposed algorithm gives above 70% accuracy for the given data.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Bing L, Chan KCC, Ou C (2014) Public sentiment analysis in twitter data for prediction of a company’s stock price movements. In: 2014 IEEE 11th IEEE international conference on e-bus engineering, pp 232–239

    Google Scholar 

  2. Trends SP, Chowdhury SG, Routh S, Chakrabarti S (2014) News analytics and sentiment analysis to predict. Int J Comput Sci Inf Technol 5(3):3595–3604

    Google Scholar 

  3. Li Q, Wang T, Li P, Liu L, Gong Q, Chen Y (2014) The effect of news and public mood on stock movements. Inf Sci (NY) 278:826–840

    Article  Google Scholar 

  4. Smailović J, Grčar M, Lavrač N, Žnidaršič M (2014) Stream-based active learning for sentiment analysis in the financial domain. Inf Sci (NY) 285(1):181–203

    Article  Google Scholar 

  5. Bhardwaj A, Narayan Y, Vanraj, Pawan, Dutta M (2015) Sentiment analysis for indian stock market prediction using sensex and nifty. Procedia Comput Sci 70:85–91

    Google Scholar 

  6. Wu DD, Zheng L, Olson DL (2014) A decision support approach for online stock forum sentiment analysis. IEEE Trans Syst Man Cybern Syst 44(8):1077–1087

    Google Scholar 

  7. Nassirtoussi AK, Aghabozorgi S, Ying Wah T, Ngo DCL (2015) Text mining of news-headlines for FOREX market prediction: a Multi-layer Dimension Reduction Algorithm with semantics and sentiment. Expert Syst Appl (1):306–324

    Google Scholar 

  8. Haddi E, Liu X, Shi Y (2013) The role of text pre-processing in sentiment analysis. Procedia Comput Sci 17:26–32

    Article  Google Scholar 

  9. Li X, Xie H, Chen L, Wang J, Deng X (2014) News impact on stock price return via sentiment analysis. Knowl-Based Syst 69(1):14–23

    Article  Google Scholar 

  10. Medhat W, Hassan A, Korashy H (2014) Sentiment analysis algorithms and applications: a survey. Ain Shams Eng J 5(4):1093–1113

    Article  Google Scholar 

  11. Nayak A, Pai MMM, Pai RM (2016) Prediction models for indian stock market. Procedia Comput Sci 89:441–449

    Article  Google Scholar 

  12. Ahuja R, Rastogi H, Choudhuri A, Garg B (2015) Stock market forecast using sentiment analysis. In: 2nd international conference on computing for sustainable global development, INDIACom, pp 1008–1010

    Google Scholar 

  13. Zhang X, Fuehres H, Gloor PA (2011) Predicting stock market indicators through twitter ‘I hope it is not as bad as I fear’. Procedia Soc Behav Sci 26(2007):55–62

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dinesh Vaghela .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Bardhan, A., Vaghela, D. (2021). Performance Analysis of Indian Stock Market via Sentiment Analysis and Historical Data. In: Kotecha, K., Piuri, V., Shah, H., Patel, R. (eds) Data Science and Intelligent Applications. Lecture Notes on Data Engineering and Communications Technologies, vol 52. Springer, Singapore. https://doi.org/10.1007/978-981-15-4474-3_3

Download citation

Publish with us

Policies and ethics