Sprache im 20. Jahrhundert. Gegenwartssprache
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One major issue in the accomplishment of contrasts in conversation is lexical choice of items which carry the semantic Ioad of the two states of affair which are represented as being opposed to one another. These items or expressions are co-selected to be understood as being contrastively related to each other. In this paper, it is argued that the activity of contrasting itself provides them with a specific local opposite meaning which they would not obtain in other contexts. Practices of contrastingare thus seen as an example of conversational activities which creatively and systematically affect situated meanings. Basedon data from various genres, such as meetings, mediation sessions and conversations, the paper discusses two practices of contrasting, their sequential construction and their interpretative effects. It is concluded that the interpretative effects of conversational contrasting rest on the sequential deployment oflinguistic resources and on the cognitive procedures of frame-based interpretation and constructing a maximally contrastive interpretation for the co-selected expressions.
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.