The structure and evolution of story networks

Area of Science:

• Narrative studies
• Network science
• Computational linguistics

Background:

• Story retellings can be modeled as networks with links representing ancestral relationships.
• Understanding the evolution of these story networks provides insights into cultural transmission processes.

Purpose of the Study:

• To provide a mechanistic understanding of the structure and evolution of story networks.
• To investigate the selection processes governing the formation of story retellings.
• To compare network growth models and identify factors influencing pre-text selection.

Main Methods:

• Construction of a story network from a diachronic corpus of Dutch "Red Riding Hood" retellings.
• Comparison with a network derived from a corpus of paper chain letters.
• Empirical analysis of age-dependent selection processes and attractiveness models in network formation.

Main Results:

• Empirical evidence for age-dependent selection, favoring shorter time spans between stories and their pre-texts.
• Demonstration that newer story versions preferentially draw from recent pre-texts.
• Identification of frequency-based, model-based, and time-decaying attractiveness as key factors in pre-text selection.

Conclusions:

• Story network evolution is significantly shaped by a preference for recent pre-texts.
• The findings support and refine existing models of network growth, highlighting specific attractiveness mechanisms.
• This study advances the understanding of how cultural narratives are transmitted and evolve over time.