dc.contributor.author
Jacobs, Arthur M.
dc.date.accessioned
2019-08-19T08:09:07Z
dc.date.available
2019-08-19T08:09:07Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/25319
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-4022
dc.description.abstract
Two computational studies provide different sentiment analyses for text segments (e.g., “fearful” passages) and figures (e.g., “Voldemort”) from the Harry Potter books (Rowling, 1997, 1998, 1999, 2000, 2003, 2005, 2007) based on a novel simple tool called SentiArt. The tool uses vector space models together with theory-guided, empirically validated label lists to compute the valence of each word in a text by locating its position in a 2d emotion potential space spanned by the words of the vector space model. After testing the tool's accuracy with empirical data from a neurocognitive poetics study, it was applied to compute emotional figure and personality profiles (inspired by the so-called “big five” personality theory) for main characters from the book series. The results of comparative analyses using different machine-learning classifiers (e.g., AdaBoost, Neural Net) show that SentiArt performs very well in predicting the emotion potential of text passages. It also produces plausible predictions regarding the emotional and personality profile of fiction characters which are correctly identified on the basis of eight character features, and it achieves a good cross-validation accuracy in classifying 100 figures into “good” vs. “bad” ones. The results are discussed with regard to potential applications of SentiArt in digital literary, applied reading and neurocognitive poetics studies such as the quantification of the hybrid hero potential of figures.
en
dc.format.extent
13 Seiten
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject
sentiment analysis
en
dc.subject
computational poetics
en
dc.subject
emotional figure profile
en
dc.subject
hybrid hero potential
en
dc.subject
machine learning
en
dc.subject
digital humanities
en
dc.subject
neuroaesthetics
en
dc.subject
literary reading
en
dc.subject.ddc
100 Philosophie und Psychologie::150 Psychologie::158 Angewandte Psychologie
dc.title
Sentiment Analysis for Words and Fiction Characters From the Perspective of Computational (Neuro-)Poetics
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation.articlenumber
53
dcterms.bibliographicCitation.doi
10.3389/frobt.2019.00053
dcterms.bibliographicCitation.journaltitle
Frontiers in Robotics and AI
dcterms.bibliographicCitation.volume
6
dcterms.bibliographicCitation.url
https://doi.org/10.3389/frobt.2019.00053
refubium.affiliation
Erziehungswissenschaft und Psychologie
refubium.affiliation.other
Arbeitsbereich Allgemeine und Neurokognitive Psychologie
refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.isPartOf.eissn
2296-9144
refubium.resourceType.provider
WoS-Alert