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Exploring digital conversation corpora with process mining

Abstract : Understanding how sentences constitute conversations is still a matter of disagreement. The automatic analysis of corpora can bring new perspectives on this issue. We show that process mining, a computer science approach for analysing human behaviour, enables the inductive identification of within-turn regularities in digital conversations. We use speech acts as a way to discretise conversations and enable the analysis. To this end, we develop a fine-grained, corpus-independent classification of speech acts that we describe and validate. We perform a manual sentence-by-sentence multi-label contextual annotation of a corpus of digital conversations and we explore it with process mining. Our results suggest that speech act theory could be extended to include typicality conditions for sequences of utterances.
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Contributor : Laëtitia Le Couédic <>
Submitted on : Tuesday, March 9, 2021 - 3:53:57 PM
Last modification on : Wednesday, March 10, 2021 - 3:35:06 AM
Long-term archiving on: : Thursday, June 10, 2021 - 7:19:49 PM


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Dario Compagno, Elena Epure, Rebecca Deneckere, Camille Salinesi. Exploring digital conversation corpora with process mining. Corpus Pragmatics, Spinger, 2018, 2, pp.193-215. ⟨10.1007/s41701-018-0030-6⟩. ⟨hal-01722928⟩



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