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Area of Science:

  • Computational Social Science
  • Network Science
  • Sociology

Background:

  • Social networks are integral to modern life, offering insights beyond individual interactions.
  • Collective community behavior, including economic trends and public reactions, can be reflected in social network mood shifts.

Purpose of the Study:

  • To develop a method for characterizing the mood steady-state of online social networks.
  • To analyze how community resilience is influenced by mood variations under external perturbations.

Main Methods:

  • Characterization of the mood steady-state in online social networks.
  • Analysis of mood dynamics in response to specific community events or perturbations.
  • Application of the developed method to three real-world social network case studies.

Main Results:

  • The study successfully characterized the mood steady-state of online social networks.
  • Demonstrated the impact of perturbations on community mood dynamics.
  • Achieved promising results in analyzing community behavior through mood variations.

Conclusions:

  • Community resilience can be effectively studied through the lens of social network mood variations.
  • The developed method provides a novel approach to understanding collective behavior and societal responses to events.