(A) study on the information source detection in social networks

Abstract

Recently, as arising of online social network services such as Facebook and Twitter, an information spread over these platforms, rapidly. Examples include the propagation of infectious diseases, the technology diffusion, the computer virus/spam infection in the Internet, and tweeting and retweeting of popular topics. Finding the source in those information spreads is one of the indispensable and useful tasks, arising in many different contexts, e.g., detecting a malicious agent, a patient zero, or an influential person, because pre-action can be taken by some authorities to limit the possible damages due to spreading of such diffused objects that are harmful, if spread in an uncontrolled manner. In this thesis, we suggest new approaches to boost up for finding the source by designing appropriate algorithms and obtain analytic results of detection performance for these algorithms. Finally, we studies that how we apply these algorithms to real environment in practice as well.