We study temporal networks of characters in literature focussing on Alice’s Adventures in Wonderland (1865) by Lewis Carroll and the anonymous La Chanson de Roland (around 1100). The former, one of the most influential pieces of nonsense literature ever written, describes the adventures of Alice in a fantasy world with logic plays interspersed along the narrative. The latter, a song of heroic deeds, depicts the Battle of Roncevaux in 778 A.D. during Charlemagne’s campaign on the Iberian Peninsula. We apply methods recently developed by Taylor et al. [Taylor, D., Myers, S. A., Clauset, A., Porter, M. A. and Mucha, P. J., Eigenvector-based centrality measures for temporal networks, CoRR (2015).] to find time-averaged eigenvector centralities, Freeman indices and vitalities of characters. We show that temporal networks are more appropriate than static ones for studying stories, as they capture features that the time-independent approaches fail to yield.

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References

1. Agarwal, A., Corvalan, A., Jensen, J. and Rambow, O., Social network analysis of alice in wonderland, in Proc. NAACL-HLT 2012 Workshop on Computational Linguistics for Literature (Association for Computational Linguistics, Montréal, Canada, 2012), pp. 88–96, Available at http://www.aclweb.org/anthology/W12-2513. Google Scholar
2. Anonymous, The Song of Roland (Hackett Publishing Company, Indianapolis and Cambridge, 2012). Google Scholar
3. Barrat, A., Barthélemy, M., Pastor-Satorras, R. and Vespignani, A., The architecture of complex weighted networks, Proc. Natl. Acad. Sci. 101 (2004) 3747–3752. Crossref, Web of Science, Google Scholar
4. Benzi, M. and Klymko, C., On the limiting behavior of parameter-dependent network centrality measures, SIAM J. Matrix Anal. Appl. 36 (2015) 686–706. Crossref, Web of Science, Google Scholar
5. C. Fenu and Higham, D. J., Block matrix formulations for evolving networks, arXiv:1511.07305v1. Google Scholar
6. Carroll, L., The Annotated Alice: Alice’s Adventures in Wonderland & Through the Looking Glass (Clarkson N. Potter, New York, 1960). Google Scholar
7. Mac Carron, P. and Kenna, R., Universal properties of mythological networks, Europhys. Lett. 99 (2012) 28002. Crossref, Google Scholar
8. Mac Carron, P. and Kenna, R., Network analysis of the íslendiga sögur — The sagas of the icelanders, Eur. Phys. J. B 86 (2013) 407. Crossref, Web of Science, Google Scholar
9. Kydros, D., Georgios, E. and Notopoulos, P., Homer’s iliad — A social network analytic approach, Int. J. Humanit. Arts Comput. 9 (2015) 115–132. Crossref, Web of Science, Google Scholar
10. Elson, D. K., Dames, N. and McKeown, K., Extracting social networks from literary fiction, in Proc. 48th Annual Meeting of the Association for Computational Linguistics (ACL 2010) (Association for Computational Linguistics, Uppsala, Sweden, 2010), Available at http://aclanthology.info/events/acl-2010. Google Scholar
11. Eagleton, T., Literary Theory. An Introduction (The University of Minnesota Press, Minneapolis, 2003). Google Scholar
12. Freeman, L. C., Centrality in social networks: Conceptual clarification, Social Netw. 1 (1979) 215–239. Crossref, Web of Science, Google Scholar
13. Gramsch, R., Das Reich als Netzwerk der Fursten (Jan Thorbecke Verlag, Ostfildern, 2012). Google Scholar
14. Holme, P., Modern temporal network theory: A colloquium, arXiv:1508.01303. Google Scholar
15. Holme, P. and Saramäki, J., Temporal networks, Phys. Rep. 519 (2012) 97–125. Crossref, Web of Science, Google Scholar
16. Koschützki, D., Lehmann, K., Peeters, L., Richter, S., Tenfelde-Podehl, D. and Zlotowski, O., Centrality indices, in Network Analysis, Brandes, U. and Erlebach, T. (eds.), Lecture Notes in Computer Science, Vol. 3418 (Springer, Berlin/Heidelberg, 2005), pp. 16–61. Crossref, Google Scholar
17. Solá, L., Romance, M., Criado, R., Flores, J., del Amo, A. G. and Boccaletti, S., Eigenvector centralities of nodes in multiplex networks, Chaos 23 (2013) 033131. Crossref, Web of Science, Google Scholar
18. Düring, M. and Stark, M., Historical network analysis, in Encyclopedia of Social Networks, ed. Barnett, G. (Sage Publishing, London, 2011). Crossref, Google Scholar
19. Moretti, F., Conjectures on world literature, New Left Rev. 1 (2000) 54–68. Google Scholar
20. Moretti, F., Graphs, Maps, Trees: Abstract Models for a Literary History (Verso, 2005). Google Scholar
21. Moretti, F., Network theory, plot analysis, New Left Rev. 80 (2011). Google Scholar
22. Newman, M., Networks: An Introduction (Oxford University Press, New York, 2010). Crossref, Google Scholar
23. Rochat, Y., Character Networks and Centrality, Ph.D. thesis, Université de Lausanne (2014). Google Scholar
24. Sack, G., haracter networks for narrative generation: Structural balance theory and the emergence of proto-narratives, in 2013 Workshop on Computational Models of Narrative, OASICS, Vol. 32 (Leibniz-Zentrum für Informatik, Dagstuhl, 2013). Google Scholar
25. Saramäki, P. H. P. J., Temporal Networks: Understanding Complex Systems (Springer Verlag, Berlin and Heidelberg, 2013). Google Scholar
26. Taylor, D., Myers, S. A., Clauset, A., Porter, M. A. and Mucha, P. J., Eigenvector-based centrality measures for temporal networks, CoRR (2015), arXiv: 1507.01266v2. Google Scholar
27. Truby, J., The Anatomy of Story (Faber and Faber, New York, 2007). Google Scholar
28. Waerzeggers, C., Social network analysis of cuneiform archives: A new approach, in Documentary Sources in Ancient Near Eastern and Greco-Roman Economic History: Methodology and Practice, Baker, H. and Jursa, M. (eds.) (Oxbow, Oxford, 2014). Crossref, Google Scholar
29. Wasserman, S. and Faust, K., Social Network Analysis: Methods and Applications, Vol. 8 (Cambridge University Press, 1994). Crossref, Google Scholar
30. Woloch, A., The One vs. The Many: Minor Characters and the Space of the Protagonist in the Novel (Princeton University Press, 2003). Google Scholar