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Realtime Online Hot Topics Prediction in Sina Weibo for News Earlier Report
Yuan, S (Yuan, Sha)1; Tao, Z (Tao, Zhe)2; Zhu, TS (Zhu, Tingshao)3; Bai, ST (Bai, Shuotian)1
First AuthorYuan, S (Yuan, Sha)
2017
Conference Name2017 IEEE 31ST INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS (AINA)
Correspondent Emailbaishuotian@hbue.edu.cn
Source Publication: International Conference on Advanced Information Networking and Applications
Issue不详
Pages599-605
Conference DateMAR 27-29, 2017
Conference PlaceTamkang Univ, Taipei, TAIWAN
Abstract

With the continuous growth of micro-blog services, Sina Weibo is increasingly found in the daily lives of ordinary Chinese individuals. More than one hundred million tweets are released in Sina Weibo everyday. By analyzing these mass data timely, media companies could learn how to generate buzz for new films, famous stars, or fashion shows more effectively. However, how to predict which topics will be the most popular search terms in Sina Weibo in realtime remains unknown. In this paper, we present a realtime hot topic prediction method in an online platform. Experiments are carried out on the platform to evaluate the proposed scheme. The results show that our model gets an average precision 44.32% and the median value is 45.83%. The proposed hot topic prediction method can predict the hot topics about 9.5 hours in average in advance.

KeywordHot Topic Prediction Sina Weibo Topic Extraction Topic Clustering
DOI10.1109/AINA.2017.66
Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.psych.ac.cn/handle/311026/26565
Collection社会与工程心理学研究室
Affiliation1.Hubei Univ Econ, Sch Informat Engn, Wuhan, Peoples R China
2.Beijing Juzi Technol Ltd, Dept Data Sci, Beijing, Peoples R China
3.Chinese Acad Sci, Inst Psychol, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Yuan, S ,Tao, Z ,Zhu, TS ,et al. Realtime Online Hot Topics Prediction in Sina Weibo for News Earlier Report[C],2017:599-605.
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