Post2Story: Automatically Generating Storylines from Microblogging Platforms

In this paper, we demonstrate Post2Story, which aims to detect events and generate storylines on microblog posts. Post2Story has several new features: (1) It proposes to employ social influence to extract events from microblogs. (2) It presents a new Event Graph Convolutional Network (E-GCN) model to learn the latent relationships among events, which can help predict the story branch of an event and link events. (3) It offers a user-friendly interface to extract and visualize the development of events. After an introduction to the system architecture and key technologies of Post2Story, we demonstrate the functionalities of Post2Story on a real dataset.