Title: Search Engine Drives the Evolution of Social Networks,
Abstract: The search engine is tightly coupled with social networks and is primarily
designed for users to acquire interested information. Specifically, the search
engine assists the information dissemination for social networks, i.e.,
enabling users to access interested contents with keywords-searching and
promoting the process of contents-transferring from the source users directly
to potential interested users. Accompanying such processes, the social network
evolves as new links emerge between users with common interests. However, there
is no clear understanding of such a "chicken-and-egg" problem, namely, new
links encourage more social interactions, and vice versa. In this paper, we aim
to quantitatively characterize the social network evolution phenomenon driven
by a search engine. First, we propose a search network model for social network
evolution. Second, we adopt two performance metrics, namely, degree
distribution and network diameter. Theoretically, we prove that the degree
distribution follows an intensified power-law, and the network diameter
shrinks. Third, we quantitatively show that the search engine accelerates the
rumor propagation in social networks. Finally, based on four real-world data
sets (i.e., CDBLP, Facebook, Weibo Tweets, P2P), we verify our theoretical
findings. Furthermore, we find that the search engine dramatically increases
the speed of rumor propagation.