Event Detection and Multi-source Propagation for Online Social Network Management

Abstract

The social network is a huge source of information, which plays an increasingly crucial role in people’s daily lives. As a form of online social network management, much information can be discovered via posts, which allows people to exchange and propagate real-life events. Multi-source event propagation involves relevant posts of interesting topics from some key users to others in microblogging network users for network management. However, there are many noisy data in traditional microblogging network management. Meanwhile few people study the spontaneous transmission of events in microblogging network management, as well as the cooperation and competition among multiple event sources. To this end, the event detection and multi-source propagation model, is established. Specifically, for efficient and accurate result of the hot event detection and propagation, we obtain the information of previous event detection and propagation to create some experience sets for the intelligent event propagation. And a multi-source events propagation model based on individual interest is established to describe the process of multi-source event information detection and dissemination, and to describe the key role of users and information characteristics in the process of communication and network management. Meanwhile, the experimental results show that the proposed intelligent multi-source events detection and propagation model can learn from previous propagation to better discover and propagate the hot events under users’ changing interest. Besides, the interaction broadens the influence scope of hot events. This helps to explain the formation of microblogging hot events dissemination, to provide a theoretical basis for the research and network management of the guiding strategy.