Abstract

Building on the work of John Mohr, I propose a new, broadly applicable approach to Discourse Role Analysis (DRA). Whereas the goal of behavioral role analysis is to identify the different kinds of actors that exist in interaction, the goal of DRA is to identify the different kinds of identities that exist in discourse. To do this, I suggest thinking of discourse roles as latent conceptions of identities composed of treatments, actions, and characteristics that are frequently concurrently associated with identities in stories. I propose a method to infer discourse roles from unstructured text data that draws on novel techniques from Natural Language Processing. This framework is leveraged to shed light on German news coverage of refugees (2010-2020), which employs a set of distinct discourse roles such as refugee as claimant of welfare benefits, refugee in distress at sea, and refugee as a criminal. I then assess how different refugee identity categories are situated within this discourse role structure. I pay particular attention to Geflüchtete, a category that emerged only recently in German discourse. Whereas initial use of Geflüchtete was motivated by a language critique that aimed at replacing the general term for refugees (Flüchtlinge), DRA indicates a process of categorical differentiation in which the category increasingly serves to distinguish different kinds of refugees.

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