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Computer-Assisted Content Analysis of Twitter Data

  • Content analysis provides a useful and multifaceted, methodological framework for Twitter analysis. CAQDAS tools support the structuring of textual data by enabling categorising and coding. Depending on the research objective, it may be appropriate to choose a mixed-methods approach that combines quantitative and qualitative elements of analysis and plays out their respective advantages to the greatest possible extent while minimising their shortcomings. In this chapter, we will discuss CAQDAS speech act analysis of tweets as an example of software-assisted content analysis. We start with some elementary thoughts on the challenges of the collection and evaluation of Twitter data before we give a brief description of the potentials and limitations of using the software QDA Miner (as one typical example for possible analysis programmes). Our focus will lie on analytical features that can be particularly helpful in speech act analysis of tweets.

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Metadaten
Author:Jessica Einspänner, Mark Dang-Anh, Caja Thimm
URN:urn:nbn:de:0168-ssoar-54492-0
ISBN:978-1-4539-1170-9
Parent Title (English):Twitter and Society
Publisher:Peter Lang
Place of publication:New York (u.a.)
Editor:Katrin Weller, Axel Bruns, Jean Burgess, Merja Mahrt, Cornelius Puschmann
Document Type:Part of a Book
Language:English
Year of first Publication:2014
Date of Publication (online):2018/06/19
Publicationstate:Postprint
Reviewstate:(Verlags)-Lektorat
Tag:CAQDAS
GND Keyword:Datenerhebung; Kommunikationsforschung; Methode; Sprechakttheorie; Twitter <Softwareplattform>
Pagenumber:21
First Page:97
Last Page:108
Dewey Decimal Classification:400 Sprache / 430 Deutsch
BDSL-Classification:Sprache im 20. Jahrhundert. Gegenwartssprache
Linguistics-Classification:Medienlinguistik
Open Access?:Ja
Licence (English):License LogoCreative Commons - Attribution-NonCommercial-ShareAlike 3.0 Unported