Intelligent Information Networks: Young Investigator Program: Modeling, Sampling, and Analyzing Adversarial Social Networks
Abstract
The major goal of this project is to propose algorithms for collecting and analyzing data from adversarial social networks. An adversarial social network is one in which some or all individuals in the network are hostile against the data collector or analyst, and so may provide information that is deliberately misleading. Specific goals within the project included the following: (1) Designing and analyzing network data collection games, including a game theoretical analysis of when data can be collected accurately. Experimental analysis of these games. (2) Creation of robust network sampling and re-sampling algorithms to collect data from adversarial social networks. Such algorithms take advantage of results from the network data collection games. Development of sampling/re-sampling algorithms that use multi-source information to reinforce and correct observed data. (3) Development of community detection and influential node location algorithms on adversarial network sampling.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 29, 2021
- Accession Number
- AD1206581
Entities
People
- Sucheta Soundarajan
Organizations
- Syracuse University