Extracting Social Networks from Literary Fiction
David K. Elson,Nicholas Dames,Kathleen R. McKeown +2 more
- pp 138-147
TLDR
The method involves character name chunking, quoted speech attribution and conversation detection given the set of quotes, which provides evidence that the majority of novels in this time period do not fit two characterizations provided by literacy scholars.Abstract:
We present a method for extracting social networks from literature, namely, nineteenth-century British novels and serials. We derive the networks from dialogue interactions, and thus our method depends on the ability to determine when two characters are in conversation. Our approach involves character name chunking, quoted speech attribution and conversation detection given the set of quotes. We extract features from the social networks and examine their correlation with one another, as well as with metadata such as the novel's setting. Our results provide evidence that the majority of novels in this time period do not fit two characterizations provided by literacy scholars. Instead, our results suggest an alternative explanation for differences in social networks.read more
Citations
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Proceedings Article
Authorship Identification for Literary Book Recommendations
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Character Profiling in 19th Century Fiction
Dimitrios Kokkinakis,Mats Malm +1 more
TL;DR: In this paper, the authors describe the way in which personal relationships between main characters in 19th century Swedish prose fiction can be identified using information guided by named entities, provided by a entity recognition system adapted to the 19 th century Swedish language characteristics.
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The one comparing narrative social network extraction techniques
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Narrative Recomposition in the Context of Digital Reading
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Modeling Dynamic Relationships Between Characters in Literary Novels
TL;DR: This work hypothesizes that relationships are dynamic and temporally evolve with the progress of the narrative, and proposes a semi-supervised framework to learn relationship sequences from fully as well as partially labeled data.
References
More filters
Journal ArticleDOI
A Coefficient of agreement for nominal Scales
TL;DR: In this article, the authors present a procedure for having two or more judges independently categorize a sample of units and determine the degree, significance, and significance of the units. But they do not discuss the extent to which these judgments are reproducible, i.e., reliable.
Proceedings ArticleDOI
Incorporating Non-local Information into Information Extraction Systems by Gibbs Sampling
TL;DR: By using simulated annealing in place of Viterbi decoding in sequence models such as HMMs, CMMs, and CRFs, it is possible to incorporate non-local structure while preserving tractable inference.
Book
The Country and the City
TL;DR: As a brilliant survey of English literature in terms of changing attitudes towards country and city, Williams' highly-acclaimed study reveals the shifting images and associations between these two traditional poles of life throughout the major developmental periods of English culture.
Proceedings Article
The Automatic Content Extraction (ACE) Program Tasks, Data, and Evaluation
George R. Doddington,Alexis Mitchell,Mark A. Przybocki,Lance Ramshaw,Stephanie Strassel,Ralph Weischedel +5 more
TL;DR: The objective of the ACE program is to develop technology to automatically infer from human language data the entities being mentioned, the relations among these entities that are directly expressed, and the events in which these entities participate.
Book
Graphs, Maps, Trees: Abstract Models for a Literary History
TL;DR: MoreMoretti as discussed by the authors argues that literature scholars should stop reading books and start counting, graphing, and mapping them instead, and offers charts, maps and time lines, developing the idea of "distant reading" into a full-blown experiment in literary history.