Universal Properties of Mythological Networks
This work addresses the challenge of quantifying mythological narratives for researchers in comparative mythology and network theory, but it is incremental as it applies existing methods to new data.
The paper tackled the problem of distinguishing real from imaginary social networks in mythological narratives using statistical mechanical tools, showing that network analysis can discriminate between them and identify anomalous features in fictional texts.
As in statistical physics, the concept of universality plays an important, albeit qualitative, role in the field of comparative mythology. Here we apply statistical mechanical tools to analyse the networks underlying three iconic mythological narratives with a view to identifying common and distinguishing quantitative features. Of the three narratives, an Anglo-Saxon and a Greek text are mostly believed by antiquarians to be partly historically based while the third, an Irish epic, is often considered to be fictional. Here we show that network analysis is able to discriminate real from imaginary social networks and place mythological narratives on the spectrum between them. Moreover, the perceived artificiality of the Irish narrative can be traced back to anomalous features associated with six characters. Considering these as amalgams of several entities or proxies, renders the plausibility of the Irish text comparable to the others from a network-theoretic point of view.