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Exploring Cultural Evolution Through Modular Dynamics in Temporal Hashtag Networks.

Yasuhiro Hashimoto1, Hiroki Sato2, Takashi Ikegami2

  • 1School of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu 965-8580, Fukushima, Japan.

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Summary
This summary is machine-generated.

This study introduces a new method to track cultural evolution on social media by analyzing hashtag networks. The approach identifies stable and changing cultural patterns over time using ensemble clustering.

Keywords:
core-periphery structurecultural evolutionensemble methodsnetwork clusteringsocial mediatemporal networks

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Area of Science:

  • Computational Social Science
  • Network Science
  • Cultural Evolution

Background:

  • Social media generates vast digital traces, offering new avenues for studying cultural dynamics.
  • Analyzing cultural evolution in complex, dynamic online networks presents significant methodological challenges.

Purpose of the Study:

  • To develop a robust methodological framework for analyzing temporal dynamics of cultural modules within hashtag co-occurrence networks.
  • To address challenges posed by dense, skewed, and highly variable cultural network data.

Main Methods:

  • Introduced a perturbation ensemble clustering approach to distinguish stable from unstable structural elements in networks.
  • Applied the Leiden algorithm to a perturbed ensemble of hashtag networks.
  • Analyzed four years of data from a major photo-sharing platform.

Main Results:

  • Identified robust core modules and their stable periphery within cultural networks.
  • Distinguished stable cultural modules from elements with unstable associations.
  • Revealed complex patterns of cultural module evolution, including stable associations and dynamic reorganizations.

Conclusions:

  • Ensemble clustering techniques effectively capture the interplay between stability and change in evolving cultural systems.
  • The proposed framework provides a powerful tool for understanding cultural evolution through digital traces.
  • This research advances the study of cultural dynamics in the digital age.