Abstract: This paper proposed an urban popular event detection and classification approach using the crowdsourced data from Sina Weibo.The detected events can be categorized into physical events or virtual events,which can be used for different applications.Our approach firstly extracts the hot words from crowd posts according to the characteristic of word frequency.With the context of hot words,hierarchical clustering is then used to obtain the description of popular events.By analyzing the three proposed features,including lexical entropy,temporal dynamics,and content originality,we applied various methods to do event classification.The experiment results indicate that all different classification methods can achieve a higher precision under our approach.

Key words: Microblogging,Popular event detection,Microblogging event classification,Mobile crowd sensing