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RNTI

MODULAD
Analyse exploratoire de corpus textuels pour le journalisme d'investigation
In EGC 2017, vol. RNTI-E-33, pp.477-480
Abstract
We propose a visual analytics tool to support investigative journalists in the exploration of
large text corpora. Our tool combines graph modularity-based diagonal biclustering to extract
high-level topics with overlapping bi-clustering to elicit fine-grained topic variants. Our co-
ordinate and multi-resolution views allows explorin high-level topics, inspecting their variants
while accessing the original content on demand.