TY - JOUR
T1 - Temporal Network Analysis of Literary Texts
AU - Prado, Sandra D.
AU - Dahmen, Silvio R.
AU - Bazzan, Ana L.C.
AU - Carron, Padraig Mac
AU - Kenna, Ralph
N1 - Publisher Copyright:
© 2016 World Scientific Publishing Company.
PY - 2016/5/1
Y1 - 2016/5/1
N2 - 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.
AB - 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.
KW - Structure and dynamics of complex networks
KW - graph theory
KW - networks and literature
UR - http://www.scopus.com/inward/record.url?scp=84986540161&partnerID=8YFLogxK
U2 - 10.1142/S0219525916500053
DO - 10.1142/S0219525916500053
M3 - Article
AN - SCOPUS:84986540161
SN - 0219-5259
VL - 19
JO - Advances in Complex Systems
JF - Advances in Complex Systems
IS - 3
M1 - 1650005
ER -