Mapping Articles on China in Wikipedia: An Inter-Language Semantic Network Analysis

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dc.contributor.authorJiang, Ke
dc.contributor.authorBenefield, Grace A.
dc.contributor.authorYang, Junfei
dc.contributor.authorBarnett, George A.
dc.date.accessioned2016-12-29T00:53:56Z
dc.date.available2016-12-29T00:53:56Z
dc.date.issued2017-01-04
dc.description.abstractThis article describes an inter-language semantic network analysis examining the differences between articles about China in the Chinese and English versions of Wikipedia. It explores the differences in the content of Wikipedia through (a) correlation analysis of semantic networks and (b) the salience of semantic concepts through their network centralities. The results suggest there is high dissimilarity between the semantic content of the English and Chinese versions of articles on China. While both pages focused on government, population, language, character, diplomatic relations, development of the economy, and science and technology, the Chinese-speaking and English-speaking contributors framed the article on China differently—according to dissimilarities in cultures, values, interests, situations, and emotions of different language groups. This research contributes to the literature and understanding of how culture of different language groups influences the process of crowdsourcing knowledge on online collaboration platforms.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2017.270
dc.identifier.isbn978-0-9981331-0-2
dc.identifier.urihttp://hdl.handle.net/10125/41425
dc.language.isoeng
dc.relation.ispartofProceedings of the 50th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectCrowdsourcing Knowledge
dc.subjectCulture
dc.subjectInter-language
dc.subjectSemantic Network Analysis
dc.subjectWikipedia
dc.titleMapping Articles on China in Wikipedia: An Inter-Language Semantic Network Analysis
dc.typeConference Paper
dc.type.dcmiText

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