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Accepted Paper:

Cartographic analysis method for thick corpora  
Desfriches Doria Orélie (Université Paris 8) Jean-Claude Domenget (University of Franche-Comté)

Paper short abstract:

We present an original methodology for qualitative mapping of controversial textual content. Part of an interdisciplinary approach, this contribution will focus on methodological aspects of this approach, but also on the functions that these maps can assume and their limits.

Paper long abstract:

For around ten years, using an experimental approach, we have been developing and testing a method in progress for cartographic analysis of thick corpora, which we have entitled “Cartographic modeling of controversies” (Desfriches Doria, 2022) . This “virtual” method (Marres, 2012) is based on the tradition of cartographic analysis, adapted to the digital context (Millette et al., 2020) at the crossroads of LIS, discourse analysis and sociology.

We will begin by briefly describing this methodology that we apply to media corpora of controversial subjects. We will continue by focusing on the nature of these kinds of polyphonic objects through examples, and the multiplicity of functions that these maps can assume.

Indeed, our cartographies constitute an analogic method of reasoning, which is here applied through digital tools. It is also a method of visual and digital processing of information to show blind spots, convergences, divergences in the positions of the actors in a debate. These maps can also be understood as a tool for reflexivity on the content of the arguments, but also as a tool for mediating the controversy.

Then we will focus on the representation of the embedded forms of enunciation in media discourses, and that the affordances of cartographic tools allow us to show through visual aspects.

Finally we will address the limits of this approach and discuss possible complementarities with more massive data processing and visualization tools.

Panel P351
Transforming methods for digital research
  Session 2 Wednesday 17 July, 2024, -