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Area of Science:

  • Information Science
  • Social Computing
  • Behavioral Economics

Background:

  • Growing interest in understanding complex human behavior, particularly behavioral asymmetry.
  • Behavioral asymmetry is a significant topic with theoretical and practical implications.
  • Need for scholarly attention on asymmetries within critical time periods.

Purpose of the Study:

  • Investigate asymmetries in human behavior during critical time periods.
  • Analyze asymmetrical human activities on social media platforms surrounding pivotal temporal moments.
  • Examine deadline-influenced behavior in social media contexts.

Main Methods:

  • Comprehensive analysis of datasets from Douban movie reviews and Weibo comments.
  • Focus on data related to a major product launch event.
  • Proposal and application of a queue model incorporating neighbor effects and critical temporal frames.

Main Results:

  • The proposed queue model effectively captures observed patterns of temporal asymmetry.
  • Demonstrated the model's accuracy in reflecting deadline-influenced human behavior.
  • Identified significant asymmetrical human activities on social media during critical time periods.

Conclusions:

  • The queue model is a valuable tool for understanding deadline impacts on social media behavior.
  • Human behavior exhibits distinct asymmetries influenced by critical temporal frames.
  • Further research can explore these dynamics in various online environments.