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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
第一作者Yuan, S (Yuan, Sha)
2017
会议名称2017 IEEE 31ST INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS (AINA)
通讯作者邮箱baishuotian@hbue.edu.cn
会议录名称: International Conference on Advanced Information Networking and Applications
期号不详
页码599-605
会议日期MAR 27-29, 2017
会议地点Tamkang Univ, Taipei, TAIWAN
摘要

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.

关键词Hot Topic Prediction Sina Weibo Topic Extraction Topic Clustering
DOI10.1109/AINA.2017.66
语种英语
引用统计
文献类型会议论文
条目标识符http://ir.psych.ac.cn/handle/311026/26565
专题社会与工程心理学研究室
作者单位1.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
推荐引用方式
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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