Difference between revisions of "Gredel2017"

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Gredel2017
BibType ARTICLE
Key Gredel2017
Author(s) Eva Gredel
Title Digital discourse analysis and Wikipedia: Bridging the gap between Foucauldian discourse analysis and digital conversation analysis
Editor(s)
Tag(s) EMCA, Wikipedia, Discourse analysis, Conversation analysis
Publisher
Year 2017
Language English
City
Month
Journal Journal of Pragmatics
Volume 115
Number
Pages 99-114
URL Link
DOI 10.1016/j.pragma.2017.02.010
ISBN
Organization
Institution
School
Type
Edition
Series
Howpublished
Book title
Chapter

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Abstract

In the last decade, analyzing online interaction rapidly gained in popularity and especially Wikipedia with its collaborative nature is a favored research object in linguistic studies. In discourse (linguistic) studies, there are some studies focusing on Wikipedia's encyclopedic article pages and others concentrating on conversational-like data on Wikipedia's talk pages. While the former can be located in the paradigm of Foucauldian discourse analysis, the latter have a rather conversation analytic approach. This paper gives an impulse to consider the convergence of data – namely the text-text convergence of article and talk pages on Wikipedia – by integrating digital conversation analysis (Giles et al., 2015) with Foucauldian discourse analysis (Spitzmüller and Warnke, 2011a). The paper begins to address this gap by conducting a detailed microanalysis on how discussions on talk pages impact on regimes of meaning on Wikipedia's article pages. The discourse fragment under investigation is the controversially discussed entry Annexation of Crimea by the Russian Federation. The considerations result in an analytic framework that integrates Foucauldian discourse analysis and digital conversation analysis. Therefore, this paper contributes to the discussion about digital conversation analysis by investigating digital discourses on Wikipedia. The microanalysis reveals communicative strategies and practices of interactivity on article pages and on corresponding talk pages. The peculiarities of Wikipedia's data will be explained, modes of analysis discussed and the challenges of the suggested integration of methods will be explored.

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