DocumentCode :
174459
Title :
Collaborative discovery of Chinese neologisms in social media
Author :
Shek Lung Lai ; Ng, Vincent Ty
Author_Institution :
Dept. of Comput., Hong Kong Polytech. Univ., Hong Kong, China
fYear :
2014
fDate :
5-8 Oct. 2014
Firstpage :
4107
Lastpage :
4112
Abstract :
The emergence of neologism in social media has bought the researchers´ attention. Traditional ways of text mining are not sufficient to handle the unique properties of messages in the new media. New methods have been developed to extract neologisms in order to help researchers to understand about community behavior in different media. In this paper, we propose a collaborative framework to detect neologisms from various social media. There are 4 different types of agents working collaboratively. Among them, the summarizing agent is using the life span parameter to confirm if an unknown character pattern is a neologism. Preliminary experiments have been performed to investigate the possible popularity patterns of some known neologisms.
Keywords :
data mining; natural language processing; social networking (online); collaborative Chinese neologism discovery; collaborative agents; community behavior; life span parameter; neologism detection; neologism extraction; social media; summarizing agent; unknown character pattern; Cleaning; Collaboration; Databases; Facebook; Market research; Media; Time-frequency analysis; neologism discovery; social media analysis; text mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics (SMC), 2014 IEEE International Conference on
Conference_Location :
San Diego, CA
Type :
conf
DOI :
10.1109/SMC.2014.6974578
Filename :
6974578
Link To Document :
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