Real-time detection and sorting of news on microblogging platforms

Abstract

Due to the increasing popularity of microblog-ging platforms (e.g., Twitter), detecting real-Time news from microblogs (e.g., tweets) has recently drawn a lot of attention. Most of the previous work on this subject detect news by analyzing propagation patterns of microblogs. This approach has two limitations: (i) many non-news microblogs (e.g. marketing activi-Ties) have propagation patterns similar to news microblogs and therefore they can be false-ly reported as news; (ii) using propagation patterns to identify news involves a time de-lay until the pattern is formed, therefore news are not detected in real time. We propose an alternative approach, which, motivated by the necessity of real-Time detection of news, does not rely on propagation of posts. More-over, we propose a real-Time sorting strategy that orders the detected news microblogs us-ing a translational approach. An experimen-Tal evaluation on a large-scale microblogging dataset demonstrates the effectiveness of our approach.