The Effect of User-generated Content Websites on Human Dynamics

Abstract

User generated content websites such as Facebook, Twitter and YouTube have become extremely popular in recent years. This trend not only changed people’s daily life but also altered the way how news and rumors spreads because of social network topologies as well as spreading dynamics of user generated content websites are quite different from traditional media platforms. In this project, I will analyze some critical factors in news and rumor spreading process by applying complex network theories, constructing models, carrying out computer simulations, and comparing the results. The results suggest that various factors including short diameter, heterogeneous degree distribution which approximately follows a power law, two-way communication channel and behavior of stiflers contribute significantly to high efficiency of diffusion process and high coverage ratio in such networks. Finally, some recommendations are put forward to make use of user generated content websites to facilitate authentic news dissemination, and on the other hand, prevent vicious rumor diffusion.