Finding Fractal Networks in Literature

Area of Science:

• Computational Linguistics
• Cognitive Science
• Fractal Mathematics

Background:

• Identifying complex linguistic structures in large text corpora is challenging.
• Understanding the underlying organizational principles of language is crucial for cognitive science.

Purpose of the Study:

• To introduce and validate the Complexity Connections in Corpuses (CCIC) hypothesis for uncovering hidden fractal word networks.
• To demonstrate the universality of these fractal structures across diverse literary works.

Main Methods:

• Utilizing a 'search-and-find' procedure based on four sub-hypotheses of CCIC.
• Employing the computer program ZIPPF to analyze and visualize fractal word networks.
• Validating CCIC by testing its sub-hypotheses on twenty-four selected literary masterpieces.

Main Results:

• Hidden fractal word-network structures were successfully identified and uncovered in corpus texts.
• The discovered hidden structures exhibited remarkable similarity across all investigated texts.
• The CCIC hypothesis and its procedures proved valid and applicable to literary corpora.

Conclusions:

• The CCIC hypothesis offers valuable tools for linguistic research and supplements existing network theories.
• The consistent fractal nature of word networks suggests a connection to the brain's text production mechanisms.
• This research opens avenues for fractal-mathematical studies of high-level brain/mind activity, supporting the idea that human verbal thinking is fractal.