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Multiple Texts as a Limiting Factor in Online Learning: Quantifying (Dis-)similarities of Knowledge Networks across Languages

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  • Alexander Mehler
  • Wahed Hemati
  • Pascal Welke
  • Maxim Konca
  • Tolga Uslu
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Article number562670
<mark>Journal publication date</mark>3/11/2020
<mark>Journal</mark>Frontiers in Education
Volume5
Publication StatusPublished
<mark>Original language</mark>English

Abstract

We test the hypothesis that the extent to which one obtains information on a given topic through Wikipedia depends on the language in which it is consulted. Controlling the size factor, we investigate this hypothesis for a number of 25 subject areas. Since Wikipedia is a central part of the web-based information landscape, this indicates a language-related, linguistic bias. The article therefore deals with the question of whether Wikipedia exhibits this kind of linguistic relativity or not. From the perspective of educational science, the article develops a computational model of the information landscape from which multiple texts are drawn as typical input of web-based reading. For this purpose, it develops a hybrid model of intra- and intertextual similarity of different parts of the information landscape and tests this model on the example of 35 languages and corresponding Wikipedias. In this way the article builds a bridge between reading research, educational science, Wikipedia research and computational linguistics.

Bibliographic note

40 pages, 13 figures, 5 tables