关键词: 突发事件, 事件检测, 微博, 博文影响力, 突发词

Abstract:

Bursty events are easy to cause public opinion and are important objects for supervision. Traditional event detection ignores the difference of influence between blog posts. This paper considers the influence of different microblog on event. For the time series Weibo data stream, this paper proposes a bursty events detection framework that combines the influence of microblog and burst words. Based on the comprehensive consideration of the influence of users and blog posts, tap the key microblogs in the window. Calculate burst words based on key microblog and historical data. Then, the latent event dataset with bursty events is constructed by means of burst word retrieval, and the bursty events are detected by clustering algorithm. Compared with two common event detection methods, experiments show that the proposed method has a significant improvement in accuracy and efficiency.

Key words: bursty events, event detection, Weibo, influence of microblog, burst word