Culturomics meets random fractal theory: Insights into long-range correlations of social and natural phenomena over the past two centuries

TL;DR

This study applies fractal analysis to culturomic data from books over two centuries, revealing that natural phenomena exhibit persistent long-range correlations, whereas social phenomena behave as nonstationary or Levy walk processes.

Contribution

It introduces fractal analysis to culturomics, providing new insights into the long-range correlations and underlying processes of social and natural phenomena.

Findings

Natural phenomena show persistent long-range correlations.

Social phenomena are characterized by nonstationary or Levy walk processes.

Fractal analysis offers new interpretations of cultural data dynamics.

Abstract

Culturomics was recently introduced as the application of high-throughput data collection and analysis to the study of human culture. Here we make use of this data by investigating fluctuations in yearly usage frequencies of specific words that describe social and natural phenomena, as derived from books that were published over the course of the past two centuries. We show that the determination of the Hurst parameter by means of fractal analysis provides fundamental insights into the nature of long-range correlations contained in the culturomic trajectories, and by doing so, offers new interpretations as to what might be the main driving forces behind the examined phenomena. Quite remarkably, we find that social and natural phenomena are governed by fundamentally different processes. While natural phenomena have properties that are typical for processes with persistent long-range correlations, social phenomena are better described as nonstationary, on-off intermittent, or Levy walk processes.