TY  - CHAP
U1  - Buchbeitrag
A1  - Einspänner, Jessica
A1  - Dang-Anh, Mark
A1  - Thimm, Caja
ED  - Weller, Katrin
ED  - Bruns, Axel
ED  - Burgess, Jean
ED  - Mahrt, Merja
ED  - Puschmann, Cornelius
T1  - Computer-Assisted Content Analysis of Twitter Data
T2  - Twitter and Society
N2  - 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.
KW  - Twitter <Softwareplattform>
KW  - Datenerhebung
KW  - Sprechakttheorie
KW  - Kommunikationsforschung
KW  - Methode
KW  - CAQDAS
Y1  - 2014
U6  - https://nbn-resolving.org/urn:nbn:de:0168-ssoar-54492-0
UN  - https://nbn-resolving.org/urn:nbn:de:0168-ssoar-54492-0
SN  - 978-1-4539-1170-9
SB  - 978-1-4539-1170-9
SP  - 97
EP  - 108
S1  - 21
PB  - Peter Lang
CY  - New York (u.a.)
ER  -