Evolution dynamics of attribute-rich social networks
Loading...
Authors
Bahulkar, Ashwin
Issue Date
2019-08
Type
Electronic thesis
Thesis
Thesis
Language
ENG
Keywords
Computer science
Alternative Title
Abstract
We study the evolution dynamics in attribute-rich social networks. We start with demonstrating how node attributes can be used to predict the formation and dissolution of new links in these networks. We introduce a method for using node preferences for different attributes to predict link formation and dissolution. We then rank these attribute according to their importance for making predictions. We find that, in the university based social network that we study, personal preferences, in particular for political views and preferences for common activities help predict link formation and dissolution. We then we look at how link prediction can be used to identify changes in network stability. We demonstrate applications to collaboration networks. We also demonstrate how to identify large scale changes in link formation patterns using link prediction.
Description
August 2019
School of Science
School of Science
Full Citation
Publisher
Rensselaer Polytechnic Institute, Troy, NY