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1
Predicting emotional links between genre, plot, and reader response ...
Sharma, Srishti
. - : Open Science Framework, 2021
Abstract:
The purpose of this article is to explore the effect of the emotions expressed in fictional stories on the emotions experienced by their readers. We use around 450 books from 9 different genres and their corresponding reviews from Goodreads. We use sentiment analysis, calculating three different types of sentiment values: the average book sentiment, the average review sentiment and the emotion story arc of each book. We use three different methods, namely, a dictionary-based approach, a transformer-based approach, and a vector-space model approach. We then define the plot type of every book by clustering the emotion story arc using k-means with Dynamic time warping Barycenter Averaging (DBA) as the distance metric. We test our hypotheses using linear regression models (ANCOVA) to analyze the covariance between the sentiment values of books and reviews. ...
Keyword:
Communication
;
Communication Technology and New Media
;
Computational Linguistics
;
computational literary studies
;
Critical and Cultural Studies
;
digital humanities
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digital literary studies
;
digital social reading
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Experimental Analysis of Behavior
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FOS Languages and literature
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FOS Psychology
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FOS Sociology
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Library and Information Science
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Linguistics
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natural language processing
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online book reviews
;
Psychology
;
reader response
;
reading impact
;
sentiment analysis
;
Social and Behavioral Sciences
;
Social Media
;
Sociology
URL:
https://osf.io/xg6d4/
https://dx.doi.org/10.17605/osf.io/xg6d4
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