Tracking conflict and emotions with a computational qualitative discourse analytic support approach.

Accurate inferences of the emotional state of conversation participants can be critical in shaping analysis and interpretation of conversational exchanges. In qualitative analyses of discourse, most labelling of the perceived emotional state of conversation participants is performed by hand, and is...

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Autores principales:	Nikodem Rybak, Daniel J Angus
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/957de5eca5c2400c815d3679f1d74359
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id	oai:doaj.org-article:957de5eca5c2400c815d3679f1d74359
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spelling	oai:doaj.org-article:957de5eca5c2400c815d3679f1d743592021-12-02T20:05:37ZTracking conflict and emotions with a computational qualitative discourse analytic support approach.1932-620310.1371/journal.pone.0251186https://doaj.org/article/957de5eca5c2400c815d3679f1d743592021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0251186https://doaj.org/toc/1932-6203Accurate inferences of the emotional state of conversation participants can be critical in shaping analysis and interpretation of conversational exchanges. In qualitative analyses of discourse, most labelling of the perceived emotional state of conversation participants is performed by hand, and is limited to selected moments where an analyst may believe that emotional information is valuable for interpretation. This reliance on manual labelling processes can have implications for repeatability and objectivity, both in terms of accuracy, but also in terms of changes in emotional state that might go unnoticed. In this paper we introduce a qualitative discourse analytic support method intended to support the labelling of emotional state of conversational participants over time. We demonstrate the utility of the technique using a suite of well-studied broadcast interviews, taking a particular focus on identifying instances of inter-speaker conflict. Our findings indicate that this two-step machine learning approach can help decode how moments of conflict arise, sustain, and are resolved through the mapping of emotion over time. We show how such a method can provide useful evidence of the change in emotional state by interlocutors which could be useful to prompt and support further in-depth study.Nikodem RybakDaniel J AngusPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 5, p e0251186 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Nikodem Rybak Daniel J Angus Tracking conflict and emotions with a computational qualitative discourse analytic support approach.
description	Accurate inferences of the emotional state of conversation participants can be critical in shaping analysis and interpretation of conversational exchanges. In qualitative analyses of discourse, most labelling of the perceived emotional state of conversation participants is performed by hand, and is limited to selected moments where an analyst may believe that emotional information is valuable for interpretation. This reliance on manual labelling processes can have implications for repeatability and objectivity, both in terms of accuracy, but also in terms of changes in emotional state that might go unnoticed. In this paper we introduce a qualitative discourse analytic support method intended to support the labelling of emotional state of conversational participants over time. We demonstrate the utility of the technique using a suite of well-studied broadcast interviews, taking a particular focus on identifying instances of inter-speaker conflict. Our findings indicate that this two-step machine learning approach can help decode how moments of conflict arise, sustain, and are resolved through the mapping of emotion over time. We show how such a method can provide useful evidence of the change in emotional state by interlocutors which could be useful to prompt and support further in-depth study.
format	article
author	Nikodem Rybak Daniel J Angus
author_facet	Nikodem Rybak Daniel J Angus
author_sort	Nikodem Rybak
title	Tracking conflict and emotions with a computational qualitative discourse analytic support approach.
title_short	Tracking conflict and emotions with a computational qualitative discourse analytic support approach.
title_full	Tracking conflict and emotions with a computational qualitative discourse analytic support approach.
title_fullStr	Tracking conflict and emotions with a computational qualitative discourse analytic support approach.
title_full_unstemmed	Tracking conflict and emotions with a computational qualitative discourse analytic support approach.
title_sort	tracking conflict and emotions with a computational qualitative discourse analytic support approach.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/957de5eca5c2400c815d3679f1d74359
work_keys_str_mv	AT nikodemrybak trackingconflictandemotionswithacomputationalqualitativediscourseanalyticsupportapproach AT danieljangus trackingconflictandemotionswithacomputationalqualitativediscourseanalyticsupportapproach
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Tracking conflict and emotions with a computational qualitative discourse analytic support approach.

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