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4. Text Mining Support to Pandemic Planning

  • 2020
  • OriginalPaper
  • Chapter
Published in:
Authors
Desheng Dash Wu
David L. Olson
Published in
Pandemic Risk Management in Operations and Finance
Publisher
Springer International Publishing

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Abstract

Text mining is a useful tool to identify sentiment. Not only it is widely used in stock market operations but it can also be applied to analyze Web content or other documents related to pandemic operations. A support vector machine is a data mining algorithm useful for certain types of data. This chapter demonstrates the use of a Web crawler to identify financial sentiment, a process that would also work for pandemic management. A support vector model is applied to a Chinese stock market index, demonstrating that technology also could be extended to pandemic planning and control.
This chapter is taken from a paper by Ren, R., Wu, D. and Liu, T. (2017). Forecasting stock market movement direction using sentiment analysis and support vector machine. IEEE Systems Journal 13(1), 760–770 with permission.

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previous chapter System Dynamics Modeling of Contagion Effects
next chapter Macroeconomic Impact
Title
Text Mining Support to Pandemic Planning
Authors
Desheng Dash Wu
David L. Olson
Copyright Year
2020
Publisher
Springer International Publishing
Book
Pandemic Risk Management in Operations and Finance

Print ISBN: 978-3-030-52196-7

Electronic ISBN: 978-3-030-52197-4

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-52197-4_4
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