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Interaction mining is about discovering and extracting insightful information from digital con- versations, namely those human–human information exchanges mediated by digital network technology. We present in this article a computational model of natural arguments and its imple- mentation for the automatic argumentative analysis of digital conversations, which allows us to produce relevant information to build interaction business analytics applications overcom- ing the limitations of standard text mining and information retrieval technology. Applications include advanced visualisations and abstractive summaries

Automatic argumentative analysis for interaction mining