User discovery based on loyalty in social networks

doi:10.11772/j.issn.1001-9081.2017.11.3095

Journal of Computer Applications ›› 2017, Vol. 37 ›› Issue (11): 3095-3100.DOI: 10.11772/j.issn.1001-9081.2017.11.3095

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User discovery based on loyalty in social networks

XUE Yun^1,2,3, LI Guohe^1,2,4, WU Weijiang^1,2,4, HONG Yunfeng⁴, ZHOU Xiaoming⁴

1. Beijing Key Lab of Data Mining for Petroleum Data, China University of Petroleum, Beijing 102249, China;
2. College of Geophysics and Information Engineering, China University of Petroleum, Beijing 102249, China;
3. Business College, Beijing Union University, Beijing 100025, China;
4. PanPass Institute of Digital Identification Management and Internet of Things, Beijing 100029, China

Received:2017-05-16 Revised:2017-06-07 Online:2017-11-11 Published:2017-11-10
Supported by:
This work is partially supported by the National High Technology Research and Development Program (863 Program) of China (2009AA062802), the National Natural Science Foundation of China (60473125,71572015), the CNPC Innovation Foundation (05E7013), the National Science and Technology Major Project (G5800-08-ZS-WX), the Science Foundation of China University of Petroleum-Beijing at Karamay (RCYJ2016B-03-001).

基于忠诚度的社交网络用户发现方法

薛云^1,2,3, 李国和^1,2,4, 吴卫江^1,2,4, 洪云峰⁴, 周晓明⁴

1. 中国石油大学(北京) 石油数据挖掘北京市重点实验室, 北京 102249;
2. 中国石油大学(北京) 地球物理与信息工程学院, 北京 102249;
3. 北京联合大学商务学院, 北京 100025;
4. 石大兆信数字身份管理与物联网技术研究院, 北京 100029

通讯作者: 薛云
作者简介:薛云(1977-),女,山西平遥人,副教授,博士研究生,主要研究方向:数据挖掘、知识发现;李国和(1965-),男,福建漳州人,教授,博士,博士生导师,主要研究方向:人工智能、机器学习、知识发现;吴卫江(1971-),男,河北唐山人,副教授,博士研究生,主要研究方向:人工智能、知识发现;洪云峰(1966-),男,福建龙岩人,主要研究方向:企业资源计划、数据管理;周晓明(1963-),男,湖北武汉人,高级工程师,主要研究方向:信息管理系统、决策支持。
基金资助:
国家863计划项目（2009AA062802）；国家自然科学基金资助项目（60473125，71572015）；中国石油（CNPC）石油科技中青年创新基金资助项目（05E7013）；国家油气重大专项子课题（G5800-08-ZS-WX）；中国石油大学（北京）克拉玛依校区科研启动基金资助项目（RCYJ2016B-03-001）。

Abstract

Abstract: Aiming at improving the users' high viscosity in social networks, an algorithm based on user loyalty in social network system was proposed. In the proposed algorithm, double Recency Frequency Monetary (RFM) model was used for mining the different loyalty kinds of users. Firstly, according to the double RFM model, the users' consumption value and behavior value were calculated dynamically and the loyalty in a certain time was got. Secondly, the typical loyal users and disloyal users were found out by using the founded standard curve and similarity calculation. Lastly, the potential loyal and disloyal users were found out by using modularity-based community discovery and independent cascade propagation model. On some microblog datasets of a social network, the quantitative representation of user loyalty was confirmed in Social Network Service (SNS), thus the users could be distinguished based on users' loyalty. The experimental results show that the proposed algorithm can be used to effectively dig out different loyalty kinds of users, and can be applied to personalized recommendation, marketing, etc. in the social network system.

Key words: social network, user discovery, loyalty, Recency Frequency Monetary (RFM), community division

摘要： 针对社交网络中提高用户的高黏性问题，提出了一种基于用户忠诚度的用户发现的算法。该算法利用双重RFM模型对用户忠诚度进行计算，挖掘出忠诚度不同分类的用户。首先，通过双重RFM模型动态计算出用户在某一时间段的消费价值与行为价值，得到用户某一时间段的忠诚度；其次，根据用户的忠诚度，确定标度曲线，利用相似度计算找到典型的忠诚用户与不忠诚用户；最后，采用基于模块度的社区发现与独立级联传播模型，发现潜在的忠诚用户与不忠诚用户。在某社交网络的微博数据集上，实现了社会性网络服务（SNS）下用户忠诚度的量化表示，获得了基于用户忠诚度的用户发现结果。实验结果表明，所提算法能够有效挖掘出基于忠诚度的用户分类，可以为社交网站针对用户的个性化推荐及营销等，提供理论支持和实用方法。

关键词: 社交网络, 用户发现, 忠诚度, RFM, 社区划分

CLC Number:

TP393

XUE Yun, LI Guohe, WU Weijiang, HONG Yunfeng, ZHOU Xiaoming. User discovery based on loyalty in social networks[J]. Journal of Computer Applications, 2017, 37(11): 3095-3100.

薛云, 李国和, 吴卫江, 洪云峰, 周晓明. 基于忠诚度的社交网络用户发现方法[J]. 计算机应用, 2017, 37(11): 3095-3100.

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User discovery based on loyalty in social networks

基于忠诚度的社交网络用户发现方法

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