Unsupervised text mining methods for literature analysis: a case study for Thomas Pynchon's V.
Year: 2013
Type: article
Abstract: We investigate the use of unsupervised text mining methods for the analysis of prose literature works, using Thomas Pynchon's novel V. as a case study. Our results suggest that such methods may be employed to reveal meaningful information regarding the novel’s structure. We report results using a wide variety of clustering algorithms, several distinct distance functions, and different visualization techniques. The application of a simple topic model is also demonstrated. We discuss the meaningfulness of our results along with the limitations of our approach, and we suggest some possible paths for further study.
Author: Christos Iraklis Tsatsoulis
Institution: Institute of Technology, Blanchardstown
Language: English
Subfield: General Social Sciences
Field: Social Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W2111481130