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Russian Summer School in Information Retrieval

RuSSIR 2014: Information Retrieval pp 297–306Cite as

Modelling Movement of Stock Market Indexes with Data from Emoticons of Twitter Users

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 505))

Abstract

The issue of using Twitter data to increase the prediction rate of stock price movements draws attention of many researchers. In this paper we examine the possibility of analyzing Twitter users’ emoticons to improve accuracy of predictions for DJIA and S&P500 stock market indices. We analyzed 1.6 billion tweets downloaded from February 13, 2013 to May 19, 2014. As a forecasting technique, we tested the Support Vector Machine (SVM), Neural Networks and Random Forest, which are commonly used for prediction tasks in finance analytics. The results of applying machine learning techniques to stock market price prediction are discussed.

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Notes

  1. 1.

    http://www.nyse.com.

  2. 2.

    http://www.nasdaq.com.

  3. 3.

    http://www.finance.yahoo.com.

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Author information

Authors and Affiliations

  1. National Research University Higher School of Economics, Nizhny Novgorod, Russia

    Alexander Porshnev, Ilya Redkin & Nikolay Karpov

Authors
  1. Alexander Porshnev
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  2. Ilya Redkin
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  3. Nikolay Karpov
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Corresponding author

Correspondence to Alexander Porshnev .

Editor information

Editors and Affiliations

  1. Ural Federal University, Yekaterinburg, Russia

    Pavel Braslavski

  2. National Research University Higher School of Economics, Nizhniy Novgorod, Russia

    Nikolay Karpov

  3. Intelligent Systems Laboratory, University of Amsterdam, Amsterdam, The Netherlands

    Marcel Worring

  4. Barcelona Media Research Foundation, Barcelona, Spain

    Yana Volkovich

  5. National Research University Higher School of Economics, Moscow, Russia

    Dmitry I. Ignatov

Appendix 1

Appendix 1

See Table 4.

Table 4. List of emoticons analyzed in the study
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Porshnev, A., Redkin, I., Karpov, N. (2015). Modelling Movement of Stock Market Indexes with Data from Emoticons of Twitter Users. In: Braslavski, P., Karpov, N., Worring, M., Volkovich, Y., Ignatov, D.I. (eds) Information Retrieval. RuSSIR 2014. Communications in Computer and Information Science, vol 505. Springer, Cham. https://doi.org/10.1007/978-3-319-25485-2_10

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  • DOI: https://doi.org/10.1007/978-3-319-25485-2_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25484-5

  • Online ISBN: 978-3-319-25485-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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