This paper demonstrates the complementarity of two types of textual analysis software, Alceste and WordMapper, to analyse a corpus of interviews. Using a top-down hierarchical classification, Alceste made apparent more homogeneous and less numerous groups of discourse than the clusters which result from a bottom-up hierarchical classification, which, on the other hand, made it possible to reveal the inter-articulation of the themes.
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