Social network analysis is applied in a variety of fields such as primatology, epidemiology, economics, and anti-terrorism. Online social networks are typically used for representing individuals and some form of relationship between them. As of July 2009, two thirds of all Internet users had joined at least one online social network, making them the platform of choice for creating and sharing content on the Internet. Following this surge in popularity, researchers have started analyzing the structure of online social networks. A deep understanding of the structure of social networks is crucial for the design and evaluation of algorithms and data structures for online social networks.
My research focusses on creating a community-based model for simulating the growth of social networks over time, investigating the quality of this model’s fit on our real-world networks, and comparing the model’s performance with existing random graph models for social networks.
In July 2010, we published a paper entitled A Community-Based Model of Online Social Networks at the 4th SNA-KDD Workshop in Washington D.C. This paper contains a description of the first version of our model for the simulation of online social network growth.
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