Exploring digital conversation corpora with process mining

Dario Compagno (1) , Elena V. Epure (2) , Rebecca Deneckere (2) , Camille Salinesi (2)

1 Crem - Centre de Recherche sur les Médiations
2 CRI - Centre de Recherche en Informatique de Paris 1

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.

Mots clés: Corpus pragmatics; Speech acts; Conversation analysis; Process mining; Multi-label annotation; Online conversations

Domaines: Sciences de l'information et de la communication

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