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Personality-based refinement for sentiment classification in microblog 期刊论文
KNOWLEDGE-BASED SYSTEMS, 2017, 卷号: 132, 期号: 132, 页码: 204-214
作者:  Lin, Junjie;  Mao, Wenji;  Zeng, Daniel D.
Adobe PDF(965Kb)  |  收藏  |  浏览/下载：554/238  |  提交时间：2018/01/04
Sentiment Classification  Social Media Analytics  Personality Prediction  Big Five Model  
Exploring the optimal granularity for market segmentation in RTB advertising via computational experiment approach 期刊论文
ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS, 2017, 卷号: 24, 期号: NA, 页码: 68-83
作者:  Qin, Rui;  Yuan, Yong;  Wang, Fei-Yue;  Yuan Yong
Adobe PDF(6997Kb)  |  收藏  |  浏览/下载：576/218  |  提交时间：2017/09/21
Real Time Bidding  Demand Side Platforms  Market Segmentation  Computational Experiment  
Who Are Your "Real" Friends: Analyzing and Distinguishing Between Offline and Online Friendships From Social Multimedia Data 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2017, 卷号: 19, 期号: 6, 页码: 1299-1313
作者:  Lu, Dongyuan;  Sang, Jitao;  Chen, Zhineng;  Xu, Min;  Mei, Tao
Adobe PDF(614Kb)  |  收藏  |  浏览/下载：228/0  |  提交时间：2017/09/12
Photo Sharing Behavior Analysis  Offline Friendship Identification  Social Multimedia Mining  
Social-Media-Based Public Policy Informatics: Sentiment and Network Analyses of US Immigration and Border Security 期刊论文
JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY, 2016, 卷号: 67, 期号: 7, 页码: 1588-1606
作者:  Chung, Wingyan;  Zeng, Daniel
收藏  |  浏览/下载：195/0  |  提交时间：2016/09/30
Public Domain Information  Knowledge Organization Systems  Network Analysis  
A model-free scheme for meme ranking in social media 期刊论文
DECISION SUPPORT SYSTEMS, 2016, 卷号: 81, 页码: 1-11
作者:  He, Saike;  Zheng, Xiaolong;  Zeng, Daniel
Adobe PDF(629Kb)  |  收藏  |  浏览/下载：317/62  |  提交时间：2016/04/03
Meme Ranking  Model-free Scheme  Transfer Entropy  
Social balance in signed networks 期刊论文
INFORMATION SYSTEMS FRONTIERS, 2015, 卷号: 17, 期号: 5, 页码: 1077-1095
作者:  Zheng, Xiaolong;  Zeng, Daniel;  Wang, Fei-Yue
Adobe PDF(761Kb)  |  收藏  |  浏览/下载：420/122  |  提交时间：2015/11/04
Social Balance  Signed Networks  Empirical Study  Dynamicsmodel