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Extracting Social Networks from Literary Fiction

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.

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Annotating characters in literary corpora: a scheme, the CHARLES tool, and an annotated novel

TL;DR: A comprehensive scheme for manually resolving mentions to characters in texts and a novel collaborative annotation tool, CHARLES (CHAracter Resolution Label-Entry System) for character annotation and similiar cross-document tagging tasks are presented.
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Identifying Speakers and Addressees in Dialogues Extracted from Literary Fiction

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Character networks and book genre classification

TL;DR: The degree distribution of character appearance is examined and a power law is found that does not depend on the literary genre or historical content and is given a plausible explanation why the previous assortativity result is not correct.
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No Permanent Friends or Enemies: Tracking Relationships between Nations from News.

TL;DR: This work extends existing models by incorporating shallow linguistics information and proposes a new automatic evaluation metric that aligns relationship dynamics with manually annotated key events, which reveals interesting regional differences in news coverage.
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Complicating the Social Networks for Better Storytelling: An Empirical Study of Chinese Historical Text and Novel

TL;DR: It is found that the social network in Romance is more complex and dynamic than that of Records, and the influence of the main characters differs, shed light on the different styles of storytelling in the two literary genres and how the historical novel complicates the social networks of characters to enrich the literariness of the story.
References
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Proceedings ArticleDOI

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Proceedings Article

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Graphs, Maps, Trees: Abstract Models for a Literary History

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