Modeling Group Interactions via Open Data Sources
Abstract
This proposal addresses an emerging challenge of developing a computational understanding of online groups and their interactions. By investigating the interactions between the groups and the social, economical, and physical forces acting on them, this project endeavors to achieve a better understanding of the operational environment by extracting pertinent values from groups of special interests. Online data sources contain massive amounts of data. The state-of-art search engines are designed to help general query-specific search and not suitable for finding disconnected online groups. The scientific and technical merits of the proposed research are demonstrated in (1) formulating novel research problems of searching disconnected online groups, (2) developing innovative mathematical and statistical models and efficient algorithms that leverage existing search engines and employ contextual information and meta data, and (3) conducting interdisciplinary scientific research that enables a new kind of search power and complementary research capabilities.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 30, 2011
- Accession Number
- ADA567932
Entities
People
- Geoff Barbier
- Huan Liu
- John Salerno
- Lei Tang
- Nitin Agarwal
- Sai Moturu
- Xufei Wang
Organizations
- Arizona State University