2 research outputs found
Multiple Texts as a Limiting Factor in Online Learning: Quantifying (Dis-)similarities of Knowledge Networks across Languages
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.Comment: 40 pages, 13 figures, 5 table
Multiple texts as a limiting factor in online learning: quantifying (dis-)similarities of knowledge networks
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 the way it measures the similarities of hypertexts, the article goes beyond existing approaches by examining their structural and semantic aspects intra- and intertextually. In this way it builds a bridge between reading research, educational science, Wikipedia research and computational linguistics