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Summary

We developed a mathematical model to understand public interest dynamics, using social media and news data. The model successfully explains responses to US violence events in 2020, revealing social sensibility insights.

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Area of Science:

  • Computational Social Science
  • Mathematical Modeling
  • Sociology

Background:

  • Public interest in societal events is influenced by media coverage and social interactions.
  • Understanding the dynamics of public response is crucial for analyzing social phenomena.

Purpose of the Study:

  • To develop and test a mathematical model for public interest dynamics.
  • To investigate the relationship between media coverage, social interactions, and public response.
  • To infer social sensibility and its correlation with human mobility.

Main Methods:

  • Constructed a simple mathematical model for public interest dynamics.
  • Utilized Twitter (tweets and retweets) as a proxy for public interest.
  • Employed news volume as a proxy for media coverage.
  • Tested the model on US violence events data from 2020.

Main Results:

  • The mathematical model demonstrated a successful fit with the collected data.
  • Inferred a measure of social sensibility from the model.
  • Found a correlation between social sensibility and human mobility data.

Conclusions:

  • The study identifies key mechanisms regulating social responses and public mobilization.
  • The model provides insights into the interplay of media, social interactions, and public interest.
  • Findings suggest a quantifiable link between social sensibility and real-world human behavior.