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A Method of Automatic Detection of Pseudoscientific Publications

  • Alexander Shvets
Part of the Advances in Intelligent Systems and Computing book series (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.

Keywords

Identifying of pseudoscientific papers Intelligent text analysis Support vector machine 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Institute for Systems Analysis of Russian Academy of SciencesMoscowRussia

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