Hdl Handle:
http://hdl.handle.net/10545/583872
Title:
Pattern recognition in narrative: Tracking emotional expression in context
Authors:
Ganz, Adam; Murtagh, Fionn ( 0000-0002-0589-6892 )
Abstract:
Using geometric data analysis, our objective is the analysis of narrative, with narrative of emotion being the focus in this work. The following two principles for analysis of emotion inform our work. Firstly, emotion is revealed not as a quality in its own right but rather through interaction. We study the 2-way relationship of Ilsa and Rick in the movie Casablanca, and the 3-way relationship of Emma, Charles and Rodolphe in the novel {\em Madame Bovary}. Secondly, emotion, that is expression of states of mind of subjects, is formed and evolves within the narrative that expresses external events and (personal, social, physical) context. In addition to the analysis methodology with key aspects that are innovative, the input data used is crucial. We use, firstly, dialogue, and secondly, broad and general description that incorporates dialogue. In a follow-on study, we apply our unsupervised narrative mapping to data streams with very low emotional expression. We map the narrative of Twitter streams. Thus we demonstrate map analysis of general narratives.
Affiliation:
University of Derby
Citation:
Murtagh, F. and Ganz, A. (2015) 'Pattern recognition in narrative: Tracking emotional expression in context', Journal of Data Mining & Digital Humanities, 647
Publisher:
Episciences.org
Journal:
Journal of Data Mining & Digital Humanities
Issue Date:
26-May-2015
URI:
http://hdl.handle.net/10545/583872
Additional Links:
http://jdmdh.episciences.org/647; http://arxiv.org/abs/1405.3539v3
Type:
Article
Language:
en
Series/Report no.:
Vol. 647
Appears in Collections:
Department of Electronics, Computing & Maths

Full metadata record

DC FieldValue Language
dc.contributor.authorGanz, Adamen
dc.contributor.authorMurtagh, Fionnen
dc.date.accessioned2015-12-14T11:37:37Zen
dc.date.available2015-12-14T11:37:37Zen
dc.date.issued2015-05-26en
dc.identifier.citationMurtagh, F. and Ganz, A. (2015) 'Pattern recognition in narrative: Tracking emotional expression in context', Journal of Data Mining & Digital Humanities, 647en
dc.identifier.otheroai:arXiv.org:1405.3539en
dc.identifier.urihttp://hdl.handle.net/10545/583872en
dc.description.abstractUsing geometric data analysis, our objective is the analysis of narrative, with narrative of emotion being the focus in this work. The following two principles for analysis of emotion inform our work. Firstly, emotion is revealed not as a quality in its own right but rather through interaction. We study the 2-way relationship of Ilsa and Rick in the movie Casablanca, and the 3-way relationship of Emma, Charles and Rodolphe in the novel {\em Madame Bovary}. Secondly, emotion, that is expression of states of mind of subjects, is formed and evolves within the narrative that expresses external events and (personal, social, physical) context. In addition to the analysis methodology with key aspects that are innovative, the input data used is crucial. We use, firstly, dialogue, and secondly, broad and general description that incorporates dialogue. In a follow-on study, we apply our unsupervised narrative mapping to data streams with very low emotional expression. We map the narrative of Twitter streams. Thus we demonstrate map analysis of general narratives.en
dc.language.isoenen
dc.publisherEpisciences.orgen
dc.relation.ispartofseriesVol. 647en
dc.relation.urlhttp://jdmdh.episciences.org/647en
dc.relation.urlhttp://arxiv.org/abs/1405.3539v3en
dc.rightsAn error occurred on the license name.en
dc.rights.uriAn error occurred getting the license - uri.en
dc.subjectNarrative data miningen
dc.subjectUnsupervised classificationen
dc.subjectHierarchical classificationen
dc.subjectCorrespondence analysisen
dc.subjectSemanticsen
dc.subjectLiteratureen
dc.subjectFilmscripten
dc.subjectTwitteren
dc.titlePattern recognition in narrative: Tracking emotional expression in contexten
dc.typeArticleen
dc.contributor.departmentUniversity of Derbyen
dc.identifier.journalJournal of Data Mining & Digital Humanitiesen
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