survey

Extraction and Analysis of Fictional Character Networks: A Survey

Authors:

Vincent Labatut,

Xavier BostAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 52, Issue 5

Article No.: 89, Pages 1 - 40

https://doi.org/10.1145/3344548

Published: 13 September 2019 Publication History

Abstract

A character network is a graph extracted from a narrative in which vertices represent characters and edges correspond to interactions between them. A number of narrative-related problems can be addressed automatically through the analysis of character networks, such as summarization, classification, or role detection. Character networks are particularly relevant when considering works of fiction (e.g., novels, plays, movies, TV series), as their exploitation allows developing information retrieval and recommendation systems. However, works of fiction possess specific properties that make these tasks harder.

This survey aims at presenting and organizing the scientific literature related to the extraction of character networks from works of fiction, as well as their analysis. We first describe the extraction process in a generic way and explain how its constituting steps are implemented in practice, depending on the medium of the narrative, the goal of the network analysis, and other factors. We then review the descriptive tools used to characterize character networks, with a focus on the way they are interpreted in this context. We illustrate the relevance of character networks by also providing a review of applications derived from their analysis. Finally, we identify the limitations of the existing approaches and the most promising perspectives.

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cover image ACM Computing Surveys

ACM Computing Surveys Volume 52, Issue 5

September 2020

791 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/3362097

Editor:
Sartaj Sahni
Department of Computer and Information Science and Engineering

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Publication History

Published: 13 September 2019

Accepted: 01 June 2019

Revised: 01 April 2019

Received: 01 November 2018

Published in CSUR Volume 52, Issue 5

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