DocumentCode :
235404
Title :
Hot topics detected from micro-bloggings based on word co-occurrence model
Author :
Long Cao ; Xin Chen ; Yuqing Zhang ; Donghui Li
Author_Institution :
China Univ. of Geosci., Beijing, China
fYear :
2014
fDate :
20-22 Oct. 2014
Firstpage :
149
Lastpage :
154
Abstract :
Micro-blogging services are used by millions of people around the world to get information and express their opinions. Detecting hot topics from Chinese micro-bloggings has vast importance to discovering rumors and guiding public opinion. In order to solve the problem of massive pieces of information on micro-bloggings platform and the feature of micro-bloggins content such as short text, in this paper a model is put forward to detect hot topics from Chinese micro-bloggings based on word co-occurrence model. The experimental results show the model can efficiently detect hot topics from Chinese micro-bloggings.
Keywords :
social networking (online); text analysis; Chinese microblogging platform; hot-topic detection; microblogging content feature; microblogging services; public opinion guidance; rumor discovery; short-text feature; word co-occurrence model; Blogs; Crawlers; Lead; Periodic structures; Graph; Hot Topic; Key Word; Micro-blogging; Opinion Leader; Word Co-occurrence;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing, Communications and IT Applications Conference (ComComAp), 2014 IEEE
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-4813-0
Type :
conf
DOI :
10.1109/ComComAp.2014.7017187
Filename :
7017187
Link To Document :
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