A Networks Approach to Mythological Epics

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Abstract

In recent years, a new approach to the analysis of ancient texts and narratives has been developed. The method draws on network science, the study of systems with interacting elements that can be represented mathematically by graphs. Network science itself is associated with statistical physics, a branch of physics which employs probability theory and statistics to capture properties of large collections of interacting entities. Many ancient narratives—from the sagas of Icelanders, through epics such as the Iliad and Beowulf, to the stories contained in medieval Irish manuscripts—record multiple interactions between sometimes vast numbers of characters and social network analysis is an excellent tool to quantify their collective properties. By capturing the interconnectedness of their underlying social structures, such narratives can be compared to each other and to other genres of literature, past and present, as well as to modern-day social networks. Here we review the main ideas behind this new approach to comparative mythology and the interrelationships of characters appearing in epic narratives. We demonstrate that, by quantitatively comparing structural properties of ancient narratives, this new approach to the humanities can deliver new comparisons, observations and insights.

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Kenna, R., & Maccarron, P. (2017). A Networks Approach to Mythological Epics. In Understanding Complex Systems (pp. 21–43). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-319-39445-9_3

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