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Maths Meets Myths: Quantitative Approaches to Ancient Narratives

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Cover of 'Maths Meets Myths: Quantitative Approaches to Ancient Narratives'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Cognitive and Network Constraints in Real Life and Literature
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    Chapter 3 A Networks Approach to Mythological Epics
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    Chapter 4 Medieval Historical, Hagiographical and Biographical Networks
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    Chapter 5 Peopling of the New World from Data on Distributions of Folklore Motifs
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    Chapter 6 Phylogenetics Meets Folklore: Bioinformatics Approaches to the Study of International Folktales
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    Chapter 7 Analyses of a Virtual World
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    Chapter 8 GhostScope: Conceptual Mapping of Supernatural Phenomena in a Large Folklore Corpus
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    Chapter 9 Complex Networks of Words in Fables
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    Chapter 10 Analysing and Restoring the Chronology of the Irish Annals
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    Chapter 11 Mapping Literate Networks in Early Medieval Ireland
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    Chapter 12 How Quantitative Methods Can Shed Light on a Problem of Comparative Mythology: The Myth of the Struggle for Supremacy Between Two Groups of Deities Reconsidered
Attention for Chapter 2: Cognitive and Network Constraints in Real Life and Literature
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Citations

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Chapter title
Cognitive and Network Constraints in Real Life and Literature
Chapter number 2
Book title
Maths Meets Myths: Quantitative Approaches to Ancient Narratives
Published by
Springer International Publishing, September 2016
DOI 10.1007/978-3-319-39445-9_2
Book ISBNs
978-3-31-939443-5, 978-3-31-939445-9
Authors

Robin Dunbar

Editors

Ralph Kenna, Máirín MacCarron, Pádraig MacCarron

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Student > Postgraduate 1 50%
Student > Master 1 50%
Readers by discipline Count As %
Mathematics 1 50%
Psychology 1 50%

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