Accession Number:

AD1085877

Title:

Prospective Analysis of Large and Complex Partially Observed Temporal Social Networks

Descriptive Note:

Technical Report,01 Aug 2012,31 Jul 2017

Corporate Author:

Temple University-of the Commonwealth System of Higher Education Philadelphia United States

Personal Author(s):

• Obradovic,Zoran

Report Date:

2018-08-14

Pagination or Media Count:

17.0

Abstract:

The objective of our study was to explore in detail the hypothesis that a unified approach is feasible for modeling large-scale temporal social networks that provide predictions and uncertainty estimates for the network structure and the properties of nodes, capture simultaneously positive and negative influences among nodes, consider simultaneously node properties of multiple types and of different temporal dynamics, address multiple kinds of interactions, allow learning in partially observed temporal graphs including predicting properties for emerging nodes. The objective of the study is completely achieved, and the results are published in 52 articles listed at the end of the report.

Descriptors:

• communities
• machine learning
• social networks
• algorithms
• learning
• accuracy

Subject Categories:

• Cybernetics
• Information Science

Distribution Statement:

APPROVED FOR PUBLIC RELEASE