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Yu-Hao Qin1, Zhi-Dan Zhao1, Shi-Min Cai1

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Human online viewing activity exhibits long-term correlations and multifractality, extending fractal properties into cyberspace. This behavior stems from event timing patterns and viewing activity correlations.

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Area of Science:

  • Complex systems
  • Network science
  • Human dynamics

Background:

  • Human activity, including online viewing, shows long-term correlations and fat-tailed distributions.
  • Fractality has been observed in human activity, but its origins in cyberspace remain unclear.

Purpose of the Study:

  • To analyze the fractality and its origins in online viewing activity from Movielens and Netflix.
  • To investigate long-term correlations at individual and communal levels in online viewing patterns.

Main Methods:

  • Detrended fluctuation analysis (DFA)
  • Multifractal detrended fluctuation analysis (MF-DFA)
  • Analysis of time series data from Movielens and Netflix viewing activity

Main Results:

  • Confirmed long-term correlations in online viewing at both individual and communal levels.
  • Demonstrated that individual correlation extent depends on activity level.
  • Identified multifractality arising from fat-tailed inter-event times and long-term correlations.

Conclusions:

  • Multifractality in online viewing is driven by fat-tailed inter-event times and long-term correlations.
  • Fractal properties of human activity now encompass cyberspace, not just physical space.
  • Findings expand the understanding of complex systems dynamics in digital environments.