Portal de Periódicos da CAPES

RETRACTED: Crowd Sensing Based Burst Computing of Events Using Social Media

2015; Hindawi Publishing Corporation; Volume: 11; Issue: 5 Linguagem: Inglês

10.1155/2015/184751

1550-1477

Zheng Xu, Yunhuai Liu, Lin Mei, Hui Zhang, Chuanping Hu,

Web Data Mining and Analysis

With the popularity of web, the internet is becoming a major information provider and poster of an event due to its real-time, open, and dynamic features. In this paper, crowd sensing based burst computation algorithm of a web event is developed in order to let the people know a web event clearly and help the social group or government process the events effectively. Different temporal features of web events are developed to provide the basics for the proposed computation algorithm. The burst power is presented to integrate the above temporal features of an event. Empirical experiments on real datasets including Google Zeitgeist and Google Trends show that the number of web pages and the average clustering coefficient can be used to detect events. The evaluations on real dataset show that the proposed function integrating the number of web pages and the average clustering coefficient can be used for event detection efficiently and correctly.