Title :
Analysis of Bulletin Board System Hot Topics Based on Multiple Keywords Combination
Author :
Shi-dong Zhu ; Xiao-hui Wu ; Jia-peng Fan
Author_Institution :
Dept. of Inf. Eng., Shenyang Inst. of Eng., Shenyang, China
Abstract :
Collection and analysis of information about network public opinion has currently become an effective means to get people thinking and recommendations by the government departments. In this paper, we presents a method of BBS(Bulletin Board System) hot topic analysis based on multiple keywords combination, this method, which use Chinese automatic word segmentation technology, firstly extracts keywords by counting the word frequency and then removes useless words from word frequency table and obtains the hot topic through the keywords positive connection. We described the method in details with a experiment which can prove the validity and rationality of the analytical method at the end of the paper.
Keywords :
government data processing; natural language processing; public information systems; text analysis; BBS; Chinese automatic word segmentation; bulletin board system hot topic analysis; information analysis; information collection; multiple keywords combination; network public opinion; word frequency; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Data mining; Electronic mail; Government; Semantics;
Conference_Titel :
Management and Service Science (MASS), 2011 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-6579-8
DOI :
10.1109/ICMSS.2011.5999066