Bursty Hot-Words Detection for Campus BBS - Geng Changxin; Zhu Xiaoguang; Nie Peiyao; Lin Peiguang (Institute of Advanced Engineering and Science, 2013)
In the monitoring of campus public opinions, hot words often reflect the latest burst hot topics within a certain period of time. Therefore, this paper takes in-depth research for bursty hot words detection. In the process of words weight calculation, we consider not only traditional features such as TF, IDF, but also the burstiness, part of speech, length, location in text and other factors. Consequently, the measurement formula of burstiness and the weight calculating formula based on symphysic multi-features are proposed. The weight calculating formula can identify the bursty hot-words quickly and accurately, and then discover the bursty events, finally realizing the early warning of campus public opinions effectively. DOI: http://dx.doi.org/10.11591/telkomnika.v11i6.2671