Visualizing conversational structure: Effects of conversation-analytical knowledge and social media experience

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Abstract

This paper explores how people understand and visualize externally a synchronous multi-threaded four-party conversation that was audio-recorded, and investigates whether conversation-analytical knowledge and/or digital skills with social media tools have an effect on the nature and complexity of the conversational structure depicted in the representation constructed. An experiment has been performed, in which 60 participants took part. Their task was to listen to a conversation, and to display it on a magnetic whiteboard in their own way. Predesigned conversation’s utterances and pictures of participants were provided, as well as markers of different colors. Both visualization process and product were coded. Coding of process included production time and relistening behavior. The product was analyzed with respect to the ordering of utterances. We used four characterizations of ordering: by chronology, by reply-to relationships, by topic, and by conversational participant. Production time and relistening behavior turn out to have varying effects on products. Results of the representations’ analysis suggest that conversation-analytical knowledge or experience with a variety of social media influence the type and the number of ordering principles used.

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Bosveld-De Smet, L., & Bakker, A. R. (2018). Visualizing conversational structure: Effects of conversation-analytical knowledge and social media experience. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10871 LNAI, pp. 484–491). Springer Verlag. https://doi.org/10.1007/978-3-319-91376-6_43

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