Interfacing Network Simulations and Empirical Data

Abstract

This project tests Social Network Models for longitudinal data against empirical data using an original statistical test to determine the effectiveness of various models at reproducing networks. The Link Probability Model (LPM) is introduced as a viable model for the reproduction of social networks in dynamic equilibrium. We survey social network simulation packages and find that Construct uses a continually updated LPM as its stochastic engine, further establishing the LPM's viability as a social network model. We use actor oriented models to estimate statistically significant behavior on empirical networks and provide guidance on future extensions into multi-agent simulation, which is a rapidly growing area of research. Our findings rely on various empirical datasets and provide analytical results on the nature and structure of the social networks observed in them.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2009
Accession Number
ADA497468

Entities

People

  • Anthony Johnson
  • Ian Mcculloh
  • Joshua Lospinoso

Organizations

  • United States Military Academy

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Command And Control
  • Computational Science
  • Data Science
  • Electronic Mail
  • Information Processing
  • Information Science
  • Knowledge Management
  • Monte Carlo Method
  • Network Science
  • Probability
  • Psychology
  • Social Networks
  • Statistical Algorithms
  • Statistical Analysis
  • Statistical Tests
  • Surveys
  • United States Military Academy

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computational Modeling and Simulation
  • Materials Science