Functional clustering of fictional narratives using Vonnegut curves

Shan Zhong () and David B. Hitchcock ()
Additional contact information
Shan Zhong: Zhejiang Ocean University
David B. Hitchcock: University of South Carolina

Advances in Data Analysis and Classification, 2024, vol. 18, issue 4, No 9, 1045-1066

Abstract: Abstract Motivated by a public suggestion by the famous novelist Kurt Vonnegut, we clustered functional data that represented sentiment curves for famous fictional stories. We analyzed text data from novels written between 1612 and 1925, and transformed them into curves measuring sentiment as a function of the percentage of elapsed contents of the novel. We employed sentence-level sentiment evaluation and nonparametric curve smoothing. Our clustering methods involved finding the optimal number of clusters, aligning curves using different chronological warping functions to account for phase and amplitude variation, and implementing functional K-means algorithms under the square root velocity framework. Our results revealed insights about patterns in fictional narratives that Vonnegut and others have suggested but not analyzed in a functional way.

Keywords: Functional data clustering; Text sentiment; SRVF (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11634-023-00567-1 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:advdac:v:18:y:2024:i:4:d:10.1007_s11634-023-00567-1

Ordering information: This journal article can be ordered from
http://www.springer. ... ds/journal/11634/PS2

DOI: 10.1007/s11634-023-00567-1

Access Statistics for this article

Advances in Data Analysis and Classification is currently edited by H.-H. Bock, W. Gaul, A. Okada, M. Vichi and C. Weihs

More articles in Advances in Data Analysis and Classification from Springer, German Classification Society - Gesellschaft für Klassifikation (GfKl), Japanese Classification Society (JCS), Classification and Data Analysis Group of the Italian Statistical Society (CLADAG), International Federation of Classification Societies (IFCS)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().