Extracting Hot Topics from Microblogging Based on Keywords Detection and Text Clustering
Bo Yi, Yong Wang, Xin Chen, Ying Wang · Applied Mechanics and Materials · 2013
Following with news and forums, microblogging becomes the third largest source of Internet public opinion. So it is necessary to do research of microblogging topic discovery. Firstly, we detect hot topics through the the keywords detection algorithm. Secondly, elect most popular microblogging text in the massive microblogging text by combining of keywords weigh and textual information entropy. Finally, using the dynamic clustering algorithm, the microblogging text elected, will form into different news topics by clustering polymerization. According to experimental validation of the true microblogging data, hot topic can be effectively detected from the text of a large number through the method.