Harbinger: An Analyzing and Predicting System for Online Social Network Users' Behavior

被引：0
|
作者：
Guo, Rui [1 ]
Wang, Hongzhi [1 ]
Zhong, Lucheng [1 ]
Li, Jianzhong [1 ]
Gao, Hong [1 ]
机构：
[1] Harbin Inst Technol, Harbin 150006, Heilongjiang, Peoples R China
来源：
DATABASE SYSTEMS FOR ADVANCED APPLICATIONS, DASFAA 2014, PT II | 2014年 / 8422卷
关键词：
Social Network; User Behavior; Message Timestamp;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Online Social Network (OSN) is one of the hottest innovations in the past years. For OSN, users' behavior is one of the important factors to study. This demonstration proposal presents Harbinger, an analyzing and predicting system for OSN users' behavior. In Harbinger, we focus on tweets' timestamps (when users post or share messages), visualize users' post behavior as well as message retweet number and build adjustable models to predict users' behavior. Predictions of users' behavior can be performed with the established behavior models and the results can be applied to many applications such as tweet crawlers and advertisements.
引用
收藏
页码：531 / 534
页数：4
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