论文标题
多个文本是在线学习中的限制因素：跨语言的知识网络的相似性
Multiple Texts as a Limiting Factor in Online Learning: Quantifying (Dis-)similarities of Knowledge Networks across Languages
论文作者
论文摘要
我们检验了以下假设：通过Wikipedia获得有关给定主题的信息的程度取决于咨询的语言。控制尺寸因子，我们研究了25个主题领域的这一假设。由于Wikipedia是基于Web的信息格局的核心部分，因此这表明与语言有关的语言偏见。因此，本文讨论了维基百科是否表现出这种语言相对论。从教育科学的角度来看，本文开发了信息格局的计算模型，从中绘制了多个文本作为基于Web的阅读的典型输入。为此，它开发了信息景观不同部分的内部和互文性相似性的混合模型，并以35种语言和相应的Wikipedias的示例来测试该模型。通过这种方式，本文在阅读研究，教育科学，维基百科研究和计算语言学之间建立了桥梁。
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.
