中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 计算技术研究所
  3. 中国科学院计算技术研究所
  4. 中国科学院计算技术研究所期刊论文
  5. 英文
Unlocking Author Power: On the Exploitation of Auxiliary Author-Retweeter Relations for Predicting Key Retweeters

文献类型：期刊论文

作者Wu, Bo2,3; Cheng, Wen-Huang1,4; Zhang, Yongdong5; Cao, Juan2; Li, Jintao2; Mei, Tao6
刊名IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
出版日期2020-03-01
卷号32期号:3页码:547-559
关键词Social network services Predictive models Prediction algorithms Computers Technological innovation Information processing Task analysis Microblogging key retweeter prediction information propagation user behavior
ISSN号1041-4347
DOI10.1109/TKDE.2018.2889664
英文摘要Retweeting is a powerful driving force in information propagation on microblogging sites. However, identifying the most effective retweeters of a message (called the "key retweeter prediction" problem) has become a significant research topic. Conventional approaches have addressed this topic from two main aspects: by analyzing either the personal attributes of microblogging users or the structures of user graph networks. However, according to sociological findings, author-retweeter dependencies also play a crucial role in influencing message propagation. In this paper, we propose a novel model to solve the key retweeter prediction problem by incorporating the auxiliary relations between a tweet author and potential retweeters. Without loss of generality, we formulate the relations from four relational factors: status relation, temporal relation, locational relation, and interactive relation. In addition, we propose a novel method, called "Relation-based Learning to Rank (RL2R)," to determine the key retweeters for a given tweet by ranking the potential retweeters in terms of their spreadability. The experimental results show that our method outperforms the state-of-the-art algorithms at top-k retweeter prediction, achieving a significant relative average improvement of 19.7-29.4 percent. These findings provide new insights for understanding user behaviors on social media for key retweeter prediction purposes.
资助项目National Key Research and Development Program of China[2016YFB0800403] ; National Nature Science Foundation of China[61525206] ; National Defense Science and Technology Fund for Distinguished Young Scholars[2017JCJQ-ZQ-022] ; Ministry of Science and Technology of Taiwan[MOST-105-2628-E-009-008-MY3] ; Ministry of Science and Technology of Taiwan[MOST-107-2218-E-009-062] ; Ministry of Science and Technology of Taiwan[MOST-107-2218-E-002-054] ; Ministry of Science and Technology of Taiwan[MOST-107-2221-E-182-025MY2]
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000526526700010
出版者IEEE COMPUTER SOC
源URL[http://119.78.100.204/handle/2XEOYT63/14232]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Zhang, Yongdong
作者单位1.Natl Chiao Tung Univ, Inst Elect, Hsinchu 30010, Taiwan
2.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.Natl Chiao Tung Univ, Dept Elect Engn, Hsinchu 30010, Taiwan
5.Univ Sci & Technol China, Sch Informat Sci & Technol, Hefei 230026, Peoples R China
6.JD AI Res, Beijing 100105, Peoples R China
推荐引用方式
GB/T 7714		 Wu, Bo,Cheng, Wen-Huang,Zhang, Yongdong,et al. Unlocking Author Power: On the Exploitation of Auxiliary Author-Retweeter Relations for Predicting Key Retweeters[J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,2020,32(3):547-559.
APA Wu, Bo,Cheng, Wen-Huang,Zhang, Yongdong,Cao, Juan,Li, Jintao,&Mei, Tao.(2020).Unlocking Author Power: On the Exploitation of Auxiliary Author-Retweeter Relations for Predicting Key Retweeters.IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,32(3),547-559.
MLA Wu, Bo,et al."Unlocking Author Power: On the Exploitation of Auxiliary Author-Retweeter Relations for Predicting Key Retweeters".IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 32.3(2020):547-559.

入库方式： OAI收割

来源：计算技术研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。