Temporal Network Analysis of Literary Texts
This work addresses literary scholars and network scientists by demonstrating the utility of temporal networks for story analysis, but it is incremental as it applies existing methods to new data.
The authors tackled the problem of analyzing character interactions in literary texts by applying temporal network methods to 'Alice's Adventures in Wonderland' and 'La Chanson de Roland', showing that temporal networks capture features missed by static approaches.
We study temporal networks of characters in literature focusing 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 and coworkers \cite{Taylor+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.