Community evolution in temporal networks
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Authors
Thompson, James
Issue Date
2015-05
Type
Electronic thesis
Thesis
Thesis
Language
ENG
Keywords
Computer science
Alternative Title
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.
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
School of Science
Full Citation
Publisher
Rensselaer Polytechnic Institute, Troy, NY