Socioscape: Real-Time Analysis of Dynamic Heterogeneous Networks In Complex Socio-Cultural Systems

Abstract

In many problems arising in social, technological, and other fields, it is often necessary to analyze populations of individuals interconnected by a network. Real-time analysis of network data is important for detecting anomaly, predicting vulnerability, and assessing the potential impact of interventions in various social and information systems. It is not unusual for network data to be large, dynamic, heterogeneous, noisy and incomplete. Each of these characteristics adds a degree of complexity to the interpretation and analysis of networks. Traditional approaches to network analysis tend to make simplistic assumptions, such as assuming that there is only a single node or edge type, or ignoring the role/mind of nodal actors and the dynamics of the networks. We intend to develop new hierarchical and dynamic Bayesian formalisms and novel graph.

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Document Details

Document Type
Technical Report
Publication Date
Oct 22, 2015
Accession Number
ADA623475

Entities

People

  • Eric P. Xing

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Autonomy
  • Cyber
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Algorithms
  • Computational Biology
  • Computational Science
  • Data Mining
  • Dynamics
  • Electronic Mail
  • Heterogeneous Networks
  • Information Processing
  • Information Science
  • Information Systems
  • Machine Learning
  • Network Science
  • Networks
  • Social Media
  • Social Networking Services
  • Social Networks

Fields of Study

  • Computer science

Readers

  • Computer Networking
  • Statistical inference.
  • Systems Analysis and Design

Technology Areas

  • AI & ML