Information Cascades in Human Networks Milo Trujillo Professor Gao - - PowerPoint PPT Presentation

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information cascades in human networks
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Information Cascades in Human Networks Milo Trujillo Professor Gao - - PowerPoint PPT Presentation

Jan 31, 2024 574 likes •788 views

Information Cascades in Human Networks Milo Trujillo Professor Gao Information Cascades Generalization of Infection Modeling Infection based on % threshold of neighbors Agent-Based model to examine heterogeneous networks Discrete

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Information Cascades in Human Networks

Milo Trujillo Professor Gao

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Information Cascades

  • Generalization of Infection Modeling
  • Infection based on % threshold of neighbors
  • Agent-Based model to examine heterogeneous networks
  • Discrete timesteps
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Variable Activation Thresholds

  • “A Simple Model of Global Cascades on Random

Networks” ~ Duncan J. Watts, PNAS 2002

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Variable Activity Times

  • “Diffusion in Networks and the Virtue of Burstiness”, M.

Akbarpour, M. O. Jackson, PNAS 2018

  • Poisson, Reversing, and Sticky Agents
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Starting Goal

  • Combine heterogeneous activation thresholds and activity times
  • Apply to scale-free networks
  • Examine resilience to targeted vs random attacks
  • How do you best spread or halt a cascade in human

communities?

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Model

  • Random or Scale-Free

networks

  • One initial agent infected
  • Contagious for 10 turns
  • Spreads to all possible

neighbors each turn

  • No “recovery”
  • Simulation ends when no

agents contagious

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First Study

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Activity Comparison

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Activity Comparison

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Activity Comparison

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Larger Scale Study

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First Study Conclusions

  • Scale Free Networks generally safer
  • Hubs act as gatekeepers, quarantine cascades
  • If a hub is susceptible, can easily spread cascade
  • Activity synchronization threatens communities
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Second Study

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Second Study

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Second Study

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Second Study Conclusions

  • Targeted attacks most effective in scale-free networks

with mid-level susceptibility to cascades

  • At high and low susceptibility, minimal difference from

random attack unless very centralized

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Future Work

  • Change Fixed Topology
  • Mix Types of Activity Patterns
  • Assortative versus Disassortative Communities