Towards a Computational Literary Science

Introduction by OpenMethods Editor (Francesca Morselli): This article introduces a novel way to unfold and discover patterns in complex texts, at the intersection between macro and micro analytics. This technique is called TIC (Transcendental Information Cascades) allows analysis of how a cast of characters is generated and managed dynamically over the duration of a text.

Our method applies the Transcendental Information Cascades (TIC) approach (Luczak-Roesch et al., 2015) to understand how emergent structures of information are generated during the unfolding of a text. It treats the text as a diachronically evolving information system and uses TIC to isolate the structural properties of that system. Theoretically, one could create an infinite number of models of any given system, depending on the dictionary one chose as the structuring element of the system (e.g., bigrams or trigrams, place names, articles or prepositions, affect words, etc.). We use character names as the structuring element. The network thus provides a visualization of the occurrence of characters and models the information structures they generate.