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Modeling narrative structure and dynamics with networks, sentiment analysis, and topic modeling

PloS one, 2019-12, Vol.14 (12), p.e0226025-e0226025 [Peer Reviewed Journal]

COPYRIGHT 2019 Public Library of Science ;COPYRIGHT 2019 Public Library of Science ;2019 Min, Park. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2019 Min, Park 2019 Min, Park ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0226025 ;PMID: 31800635

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Title:
Modeling narrative structure and dynamics with networks, sentiment analysis, and topic modeling
Author: Min, Semi ; Park, Juyong
Gross, Thilo
Subjects: Analysis ; Biology and Life Sciences ; Computational linguistics ; Computer and Information Sciences ; Computer applications ; Culture ; Data mining ; Dynamic structural analysis ; Ecology and Environmental Sciences ; Engineering and Technology ; Growth patterns ; Hugo, Victor ; Human communication ; Humanities ; Humans ; Language ; Language processing ; Linguistics ; Models, Theoretical ; Mythology ; Narration ; Narratives ; Natural language ; Natural language interfaces ; Natural language processing ; Physical Sciences ; Reading ; Sentiment analysis ; Social networks ; Social Sciences ; Storytelling
Is Part Of: PloS one, 2019-12, Vol.14 (12), p.e0226025-e0226025
Description: Human communication is invariably executed in the form of a narrative, an account of connected events comprising characters, actions, and settings. A coherent and well-structured narrative is therefore essential for effective communication, confusion caused by a haphazard attempt at storytelling being a common experience. This also suggests that a scientific understanding of how a narrative is formed and delivered is key to understanding human communication and dialog. Here we show that the definition of a narrative lends itself naturally to network-based modeling and analysis, and they can be further enriched by incorporating various text analysis methods from computational linguistics. We model the temporally unfolding nature of narrative as a dynamical growing network of nodes and edges representing characters and interactions, which allows us to characterize the story progression using the network growth pattern. We also introduce the concept of an interaction map between characters based on associated sentiments and topics identified from the text that characterize their relationships explicitly. We demonstrate the methods via application to Victor Hugo's Les Misérables. Going beyond simple, aggregate occurrence-based methods for narrative representation and analysis, our proposed methods show promise in uncovering its essential nature of a highly complex, dynamic system that reflects the rich structure of human interaction and communication.
Publisher: United States: Public Library of Science
Language: English
Identifier: ISSN: 1932-6203
EISSN: 1932-6203
DOI: 10.1371/journal.pone.0226025
PMID: 31800635
Source: Public Library of Science (PLoS) Journals Open Access
Geneva Foundation Free Medical Journals at publisher websites
MEDLINE
PubMed Central（OA）
ProQuest Central
DOAJ Directory of Open Access Journals

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Modeling narrative structure and dynamics with networks, sentiment analysis, and topic modeling

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