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  5. Windows on Waverley: exploring the effect of variations in the construction of literary social networks
 
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Windows on Waverley: exploring the effect of variations in the construction of literary social networks

Author(s)
Wade, Karen  
Grayson, Siobhán  
Uri
http://hdl.handle.net/10197/9020
Date Issued
2016-09-10
Date Available
2017-10-27T12:12:23Z
Abstract
In recent years, social network analysis (SNA) has become increasingly popular as a quantitative approach to the examination of literary works, allowing researchers to generate abstract models of character groupings and interactions that appear in texts, and providing new opportunities for the evaluation of theories about communities and societies in literature. The social networks that are generated for a given novel, however, will differ considerably depending on what choices are made in relation to their construction: what types of interactions or co-occurrences are examined, what characters or other entities are considered, whether full texts or subsections such as chapters are investigated, and what automated methods are utilised for extracting character data, among others. This paper examines the effect of varying one specific aspect of network construction, by applying different "sliding window" strategies in order to create variations on social networks in three rather different early 19th-century novels: Pride and Prejudice (1813), Waverley (1814), and Frankenstein (1818). Three window strategies (collinear, co-planar and combination) are discussed, each of which captures qualitatively different social links between characters. We argue that the resulting networks yield different insights into a variety of aspects of the novels' construction, including narrative style and interactions between characters of different social class. We also suggest that rather than seeking to determine a single best-practice methodology for literary SNA, it may instead be illuminating to experiment with different approaches to the modelling of literary texts as social networks.
Sponsorship
Irish Research Council
Science Foundation Ireland
Other Sponsorship
Insight Research Centre
Type of Material
Conference Publication
Subjects

Machine Learning & St...

Web versions
https://hridigital.shef.ac.uk/dhc/2016/paper/74
Language
English
Status of Item
Peer reviewed
Conference Details
Digital Humanities Congress. University of Sheffield, United Kingdom
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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insight_publication.pdf

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1.42 MB

Format

Adobe PDF

Checksum (MD5)

e6e41621155fe65f3ae2c1a64ddab217

Owning collection
Insight Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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