Min Hu


Complex networks have been studied for a long time in order to understand various real-world complex systems around us. Complex systems, such as the WWW, the movie-actor network, social networks and neural networks, are systems made of many non-identical elements connected by diverse interactions. The study of the network topology is one of important issues on the way of exploring such systems, because the structure always affects the system function. Traditionally, these systems have been modeled as either completely ordered graphs or completely random graphs. Until recently, some surprising empirical results in the field of complex networks, like 19 clicks of the web s diameter and 6 degrees of separation in social networks, show us the small-world phenomena existing in some large sparse networks. This finding motivates the interest in small-world networks. The objective of the project is to study the properties of small-world networks and the network evolution over time via experiments on a movie actor collaboration network; to find their different characteristics by comparing small-world networks with random networks; and to analyze the factors that result in such differences. The properties of small-world networks discussed here include small diameter, sparseness, clustering, giant component, power-law degree distribution and short path discovery. Also, four existing network models are studied in this project: Watts-Strogatz Small-world model, Erd s R nyi Random-graph model, A.-L. Barab si Scale-free model and Jon Kleinberg Small-world model.

Publication Date


Document Type

Master's Project

Student Type


Department, Program, or Center

Computer Science (GCCIS)


Radziszowski, Stanislaw - Chair

Advisor/Committee Member

Gaborski, Roger

Advisor/Committee Member

Homan, Christopher


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