Seminar Details

In the natural network structure, especially in the social networks, community structures are one of the prominent properties. An extreme case of that is when the network is partitioned into two camps with opposing relationships. In this talk, I will introduce our co-evolution model for both dynamics of opinions (people's views on a variety of topics) and dynamics of social appraisals (the approval or disapproval towards each other). It leads to the formation of communities in the networks. The opinion of an individual is updated by the weighted average of opinions from neighbors. And the tie appraisal of two nodes is updated with a margin proportional to the agreement of their opinions.

We show that with favorable conditions on the initial opinion and edge appraisal values, the system stabilizes at finite time, at which edge weights have stable signs (positive or negative), and structure balance is achieved (the multiplication of weights on any triangle is non-negative). Some real-world examples are demonstrated using this co-evolution model. The stable final state is matched with the camps partition in the real world. This explains that community structure naturally evolves as an outcome of the co-evolution model. The model sheds light on why community structure emerges and becomes a widely observed, sustainable property in complex networks.

Bio: Haotian Wang is a Ph.D. candidate in the department of computer science at Rutgers University. His research interests include: computational geometry, algorithm design, and networking application.