Using cellular automata to model social networking behavior

Modeling human behavior to reflect the social dynamics is a challenging task. Currently, social networking is an important facet of our lives and it is important to understand how users behave in networking sites. In this paper, we model social networking behavior using cellular automata (CA) to understand dynamic aspects of an individual as well as of a group of individuals in terms of relations and evolution. CA is a powerful technique for modeling interactions between nodes with discrete states which are similar to users of social networking sites. We explore the ability to model the user behaviors of Twitter based on CA properties.