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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Notes
- 1.
We distinguish Beowulf the narrative from Beowulf the character by writing the former in italics.
- 2.
The number of characters alone is not very informative in the current context; we are interested in interactions and, for social networks, positive interactions in particular. In the Táin, for example, many characters—some named and some unnamed—are introduced to be immediately killed off by Cúchulainn. We keep only a representative amount of named characters. Thus, for the full network, the values of N in Table 1 may be interpreted as minimum sizes.
- 3.
References
Albert, R., & Barabási, A.-L. (2002). Statistical mechanics of complex networks. Reviews of Modern Physics, 74, 47–97.
Albert, R., Jeong, H., & Barabási, A.-L. (2000). Error and attack tolerance of complex networks. Nature, 406, 378–382.
Amaral, L. A. N., Scala, A., Barthélémy, M., & Stanley, H. E. (2000). Classes of small-world networks. Proceedings of the National Academy of Sciences of the United States of America, 97, 11149–11152.
Anderson, C. E. (1999). Formation and resolution of ideological contrast in the early history of Scandinavia. PhD Thesis, The University of Cambridge, Cambridge.
Antal, T., Krapivsky, P. L., & Redner, S. (2006). Social balance on networks: The dynamics of friendship and enmity. Physica D, 224, 130–136.
Buldyrev, S. V., Parshani, R., Paul, G., Stanley, H. E., & Havlin, S. (2010). Catastrophic cascade of failures in interdependent networks. Nature, 464, 984–985.
Campbell, J. (1949). The hero with a thousand faces. Princeton: Princeton University Press.
Carson, C. (2007). The Táin: A new translation of the Táin Bó Cúailnge. London: Penguin.
Cartwright, D., & Harary, F. (1956). Structural balance: A generalization of Heider’s theory. Psychological Review, 63, 277–293.
Chambers, R. W. (1959). Beowulf: An introduction. Cambridge: Cambridge University Press.
Cheswick, W., & Burch, H. (1999). Mapping the internet. Computer, 32, 97–98.
Davis, G. F., Yoo, M., & Baker, W. E. (2003). The small world of the American corporate elite, 1982–2001. Strategic Organization, 1, 301–326.
Dillon, M. (1948). Early Irish literature. Chicago: University of Chicago Press.
Dunne, J. A., Williams, R. J., & Martinez, N. D. (2004). Network structure and robustness of marine food webs. Marine Ecology Progress Series, 273, 291–302.
Estrada, E. (2011). The structure of complex networks: Theory and applications. Oxford: Oxford University Press.
Finley, M. I. (1954). The world of Odysseus. New York: Viking.
Fortunato, S. (2010). Community detection in graphs. Physics Reports, 486, 75–174.
Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40, 35–41.
Girvan, M., & Newman, M. E. J. (2002). Community structure in social and biological networks. Proceedings of the National Academy of Sciences of the United States of America, 99, 7821–7826.
Gleiser, P. M. (2007). How to become a superhero. Journal of Statistical Mechanics: Theory and Experiment, P09020.
Gleiser, P. M., & Danon, L. (2003). Community structure in jazz. Advances in Complex Systems, 6, 565–573.
Heider, F. (1946). Attitudes and cognitive organization. The Journal of Psychology, 21, 107–112.
Holovatch, Y., & Palchykov, V. (2007). Mykyta the Fox and networks of language. arXiv preprint: arXiv:0705.1298.
Jackson, K. H. (1964). The oldest Irish tradition: A window on the Iron Age. Cambridge: Cambridge University Press.
Kinsella, T. (1969). The Táin. Oxford: Oxford University Press.
Klaeber, F. (1950). Beowulf and the fight at Finnsburg. Lexington, MA: D. C. Heath.
Korfmann, M. (2004). Was there a Trojan war? Archaeology, 57, 36–38.
Kraft, J. C., Rapp, G., Kayan, I., & Luce, J. V. (2003). Harbor areas at ancient troy: Sedimentology and geomorphology complement Homer’s Iliad. Geology, 31, 163–166.
Kujawski, B., & Abell, P. (2011). Virtual communities?: The Middle East revolutions at the guardian forum: Comment is free. European Physics Journal B, 83, 525–529.
Kuperman, M., & Abramson, G. (2001). Small world effect in an epidemiological model. Physical Review Letters, 86, 2909.
MacCarron, P. (2014). A network theoretic approach to comparative mythology. PhD Thesis, Coventry University, Coventry.
MacCarron, P., & Kenna, R. (2012). Universal properties of mythological networks. Europhysics Letters, 99, 28002.
MacCarron, P., & Kenna, R. (2013). Network analysis of the Íslendinga sögur—the Sagas of Icelanders. European Physical Journal B, 86, 407.
Milgram, S. (1967). The small world problem. Psychology Today, 2, 60–67.
Moore, C., & Newman, M. E. J. (2000). Epidemics and percolation in small-world networks. Physical Review E, 61, 5678.
Moreno, J. L. (1934). Who shall survive? A new approach to the problem of human interrelations. Washington DC: Nervous and Mental Disease Publishing Co.
Myers, C. R. (2003). Software systems as complex networks: Structure, function, and evolvability of software collaboration graphs. Physical Review E, 68, 046116.
Newman, M. E. J. (2001). The structure of scientific collaboration networks. Proceedings of the National Academy of Sciences of the United States of America, 98, 404–409.
Newman, M. E. J. (2002). Assortative mixing in networks. Physical Review Letters, 89, 208701.
Newman, M. E. J. (2006). Finding community structure in networks using the eigenvectors of matrices. Physical Review E, 74, 036104.
Newman, M. E. J. (2010). Networks: An introduction. Oxford: Oxford University Press.
Newman, M. E. J., & Girvan, M. (2004). Finding and evaluating community structure in networks. Physical Review E, 69, 026113.
Newman, M. E. J., & Park, J. (2003). Why social networks are different from other types of networks. Physical Review E, 68, 036122.
O’Donoghue, H. (2004). Old Norse-Icelandic literature: A short introduction. Oxford: Blackwell Publishing.
O’Rahilly, T. F. (1946). Early Irish history and mythology. Dublin: Dublin Institute of Advanced Studies.
Paczuski, M., & Hughes, D. (2004). A heavenly example of scale-free networks and self-organized criticality. Physica A, 342, 158–163.
Papamarinopoulos, S. P., Preka-Papadema, P., Antonopoulos, P., Mitropetrou, H., Tsironi, A., & Mitropetros, P. (2012). A new astronomical dating of Odysseus’ return to Ithaca. Mediterranean Archaeology and Archaeometry, 12, 117–128.
Scala, A., Amaral, L. A. N., & Barthélémy, M. (2001). Small-world networks and the conformation space of a short lattice polymer chain. Europhysics Letters, 55, 594–600.
Schweitzer, F., Fagiolo, G., Sornette, D., Vega-Redondo, F., & White, D. R. (2009). Economic networks: What do we know and what do we need to know? Advances in Complex Systems, 12, 407–422.
von Ferber, C., Berche, B., Holovatch, T., & Holovatch, Y. (2012). A tale of two cities: Vulnerabilities of the London and Paris transit networks. Journal of Transportation Security, 5, 199–216.
Wassermann, F., & Faust, K. (1994). Social network analysis. Cambridge: Cambridge University Press.
Wood, M. (1998). In search of the Trojan War. Berkeley: University of California Press.
Acknowledgements
We thank Silvio Dahmen and Joseph Yose for discussions which helped inform the content and presentation of this chapter.
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Kenna, R., MacCarron, P. (2017). A Networks Approach to Mythological Epics. In: Kenna, R., MacCarron, M., MacCarron, P. (eds) Maths Meets Myths: Quantitative Approaches to Ancient Narratives. Understanding Complex Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-39445-9_3
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