Community evolution in temporal networks

Authors
Thompson, James
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Other Contributors
Magdon-Ismail, Malik
Goldberg, Mark
Szymanśki, Bolesław
Wallace, William A., 1935-
Issue Date
2015-05
Keywords
Computer science
Degree
PhD
Terms of Use
Attribution-NonCommercial-NoDerivs 3.0 United States
This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.
Full Citation
Abstract
The purpose of this research is to study the structure of social networks with an added temporal element. Specifically, we examine dynamic community behavior within social networks. We base our experiments on a simple theoretical foundation which allows us to efficiently identify dynamic community evolutions. Based on this framework, we empirically study evolutions in large social networks and structural features of evolutions across all networks. Results show that structural properties remain similar across multiple social networks and it is possible to correlate the lifespan of a community to specific features of its early evolution.
We also develop a framework for generating social networks with structures similar to those found in real world systems. Using this framework, we examine the behavior of evolution detection algorithms in full networks and more isolated situations. Finally we examine the robustness of our developed community evolution tracking framework in noisy systems.
Description
May 2015
School of Science
Department
Dept. of Computer Science
Publisher
Rensselaer Polytechnic Institute, Troy, NY
Relationships
Rensselaer Theses and Dissertations Online Collection
Access
CC BY-NC-ND. Users may download and share copies with attribution in accordance with a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License. No commercial use or derivatives are permitted without the explicit approval of the author.