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Identifying top Chinese network buzzwords from social media big data set based on time-distribution features

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成果类型:
会议论文
作者:
Tang, Yongli*;He, Tingting(何婷婷);Li, Bo;Hu, Xiaohua
通讯作者:
Tang, Yongli
作者机构:
[He, Tingting; Li, Bo; Tang, Yongli] Cent China Normal Univ, Sch Comp, Wuhan, Peoples R China.
[Hu, Xiaohua] Drexel Univ, Coll Informat Sci & Technol, Philadelphia, PA 19104 USA.
通讯机构:
[Tang, Yongli] C
Cent China Normal Univ, Sch Comp, Wuhan, Peoples R China.
语种:
英文
关键词:
buzzword;time-distribution;language model;KL divergence
期刊:
2014 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA)
ISSN:
2639-1589
年:
2014
页码:
924-931
会议名称:
IEEE International Conference on Big Data
会议论文集名称:
IEEE International Conference on Big Data
会议时间:
OCT 27-30, 2014
会议地点:
Washington, DC
会议主办单位:
[Tang, Yongli;He, Tingting;Li, Bo] Cent China Normal Univ, Sch Comp, Wuhan, Peoples R China.^[Hu, Xiaohua] Drexel Univ, Coll Informat Sci & Technol, Philadelphia, PA 19104 USA.
会议赞助商:
IEEE, IEEE Comp Soc, ELSEVIER, Natl Sci Fdn, CISCO, CCF
主编:
Lin, J Hu, XH Chang, W Nambiar, R Aggarwal, C Cercone, N Honavar, V Huan, J Mobasher, B Pyne, S
出版地:
345 E 47TH ST, NEW YORK, NY 10017 USA
出版者:
IEEE
ISBN:
978-1-4799-5666-1
机构署名:
本校为第一且通讯机构
院系归属:
计算机学院
摘要:
Buzzwords are the main embodiment of internet culture, which play an important role in public opinion analysis, social focus tracking and language evolution study. At present, questionnaire has been wildly used as a standard method to obtain network buzzwords, which is subjective and costly. In this paper, we will propose a novel algorithm relying on the time-distribution feature of words and a KL-divergence measure to estimate words' popularity so as to figure out buzzwords in a specific period. The time-distribution feature simply states the fact that buzzwords' usage has a sharp increase du...

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