Real-time Detection and Sorting of News on Microblogging Platforms.
PACLIC(2015)
摘要
Due to the increasing popularity of microblogging platforms (e.g., Twitter), detecting realtime 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 activities) have propagation patterns similar to news microblogs and therefore they can be falsely reported as news; (ii) using propagation patterns to identify news involves a time delay 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. Moreover, we propose a real-time sorting strategy that orders the detected news microblogs using a translational approach. An experimental evaluation on a large-scale microblogging dataset demonstrates the effectiveness of our approach.
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