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A Method of Automatic Detection of Pseudoscientific Publications

  • Conference paper
Intelligent Systems'2014

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 323))

Abstract

Currently, pseudoscientific theories are actively promoted being published in a large amount of papers. They appear in mass media, in patents and even in scientific journals, and it is rather difficult for non-expert to distinguish scientific paper from pseudoscientific. A method for identifying pseudoscientific publications based on automatic text analysis is proposed. At first, the text is partitioned into small fragments consisting of several paragraphs. Then feature extraction occurs using an automatic linguistic analysis and classification of text fragments is implemented by support vector machines. Experiments show that the method divides scientific and pseudoscientific publications into different classes with high accuracy.

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Author information

Authors and Affiliations

  1. Institute for Systems Analysis of Russian Academy of Sciences, Moscow, Russia

    Alexander Shvets

Authors
  1. Alexander Shvets
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Corresponding author

Correspondence to Alexander Shvets .

Editor information

Editors and Affiliations

  1. Ford Motor Company, Research & Advanced Engineering, Dearborn, Mississippi, USA

    D. Filev

  2. Industrial Research Institute for Automation and Measurements (PIAP), Warsaw, Poland

    J. Jabłkowski

  3. Polish Academy of Sciences, Systems Research Institute, Warsaw, Poland

    J. Kacprzyk

  4. Polish Academy of Sciences and WIT - Warsaw School of Information Technology, Systems Research Institute, Warsaw, Poland

    M. Krawczak

  5. Bulgarian Academy of Sciences, Institute of Information and Communication, Sofia, Bulgaria

    I. Popchev

  6. Department of Computer Engineering, Częstochowa University of Technology, Częstochowa, Poland

    L. Rutkowski

  7. Bulgarian Academy of Sciences, Institute of Information and Communication Technologies, Sofia, Bulgaria

    V. Sgurev

  8. Department of Computer and Information Technologies, “Prof. Assen Zlatarov" University Faculty of Technical Sciences, Bourgas, Bulgaria

    E. Sotirova

  9. Industrial Research Institute for Automation and Measurements (PIAP), Warsaw, Poland

    P. Szynkarczyk

  10. Polish Academy of Sciences, Systems Research Institute, Warsaw, Poland

    S. Zadrozny

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© 2015 Springer International Publishing Switzerland

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Shvets, A. (2015). A Method of Automatic Detection of Pseudoscientific Publications. In: Filev, D., et al. Intelligent Systems'2014. Advances in Intelligent Systems and Computing, vol 323. Springer, Cham. https://doi.org/10.1007/978-3-319-11310-4_46

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  • DOI: https://doi.org/10.1007/978-3-319-11310-4_46

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11309-8

  • Online ISBN: 978-3-319-11310-4

  • eBook Packages: EngineeringEngineering (R0)

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