Information tracing model based on PageRank

doi:10.11959/j.issn.2096-109x.2017.00190

网络与信息安全学报 ›› 2017, Vol. 3 ›› Issue (8): 68-76.doi: 10.11959/j.issn.2096-109x.2017.00190

• 学术论文 • 上一篇

Information tracing model based on PageRank

LI Qian^1,²(),LAI Jia-wei²,XIAO Yun-peng²,WU Bin¹

¹ Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia,Beijing University of Posts and Telecommunications,Beijing 100876,China
² Chongqing Engineering Laboratory of Network and Information Security,Chongqing University of Posts and Telecommunications,Chongqing 400065,China

修回日期:2017-07-05 出版日期:2017-08-01 发布日期:2017-12-26
作者简介:LI Qian (1980-),born in Chongqing. She is working on her Ph.D. degree at Beijing university of posts and telecommunications. Her research interests include social network analysis and information dissemination dynamics.|LAI Jiawei (1992-),born in Jiangxi. She is working on her master degree at Chongqing university of posts and telecommunications. Her research interests include social network analysis and machine learning.|XIAO Yunpeng (1979-),born in Anhui. He received his Ph.D degree of computer science from Beijing university of posts and telecommunications. He is an associate professor in Chongqing university of posts and telecommunications. His research interests include social network analysis and machine learning.|Wu Bin (1969-),born in Hunan. He received his Ph.D degree of institute of computing Chinese academy of sciences in 2002. He is a professor in Beijing university of posts and telecommunications. His research interests include complex network,data mining,massive data parallel processing,visual analysis and telecom customer relationship management.
基金资助:
National Key Basic Research Program (973 program) of China(2013CB329606);Chongqing Science and Technology Commission Project(cstc2017jcyjAX0099);Science and Technology Research Program of the Chongqing Municipal Education Committee(KJ1500425);Ministry of Education of China and China Mobile Research Fund(MCM20130351)

Qian LI^1,²(),Jia-wei LAI²,Yun-peng XIAO²,Bin WU¹

Revised:2017-07-05 Online:2017-08-01 Published:2017-12-26

摘要/Abstract

关键词: social network, hot topic, information tracing, PageRank

Abstract:

In social network,original publisher and important nodes in the diffusion process can be traced by analyzing the spreading network of a hot topic.The participated users and spreading network structure of a hot topic build an information tracing model,which mines the source and important diffusion nodes.Firstly,it analyzed the development trend of a hot topic and extracts the users involved.Secondly,it established a user network according to the following relationship of the users involved.Thirdly,the contribution rate of users on the development of the hot topic was initialized,and the PageRank algorithm was used to construct the information tracing model.Finally,the Top k users were selected as the information publisher and important users of the hot topic according to the contribution rate.Experimental results showed that our model can effectively discover the hot topic of the publisher and important users.

LI Qian,LAI Jia-wei,XIAO Yun-peng,WU Bin. Information tracing model based on PageRank[J]. 网络与信息安全学报, 2017, 3(8): 68-76.

Qian LI,Jia-wei LAI,Yun-peng XIAO,Bin WU. [J]. Chinese Journal of Network and Information Security, 2017, 3(8): 68-76.

图/表 11

Fig.1

Fig.2

Fig.3

Fig.4

Fig.5

Table 1

Fig.6

Table 2

Table 3

Table 4

Table 5

参考文献 14

[1]	OPSAHL T , AGNEESSENS F , SKVORETZ J . Node centrality in weighted networks:generalizing degree and shortest paths[J]. Social networks, 2010,32: 245-251.
[2]	OLSEN P W , LABOUSEUR A G , HWAN J H . Efficient top-k closeness centrality search[C]// Data Engineering (ICDE). 2014: 196-207.
[3]	RIONDATO M , KORNAROPOULOS E M . Fast approximation of betweenness centrality through sampling[J]. Data Mining and Knowledge Discovery,New York, 2016,30: 438-475.
[4]	MORONE F , MAKSE H A . Influence maximization in complex networks through optimal percolation[J]. Nature, 2015,524: 65-68.
[5]	AKOGLU L , TONG H , KOUTRA D . Graph based anomaly detection and description:a survey[J]. Data Mining and Knowledge Discovery, 2015,29: 626-688.
[6]	BAO J , ZHENG Y , WILKIE D ,et al. Recommendations in location-based social networks:a survey[J]. GeoInformatica, 2015,19: 525-565.
[7]	MA N , LIU Y . SuperedgeRank algorithm and its application in identifying opinion leader of online public opinion supernetwork[J]. Expert Systems with Applications, 2014(3): 1357-1368.
[8]	ALEAHMAD A , KARISANI P , RAHGOZAR M ,et al. OLFinder:Finding opinion leaders in online social networks[J]. Journal of Information Science, 2015,42(9): 659-674.
[9]	ROMERO D M , GALUBA W , ASUR S ,et al. Influence and Passivity in Social Media[C]// Joint European Conference on Machine Learning and Knowledge Discovery in Databases. 2011: 18-33.
[10]	WENG J S , LIM P E , JIANG J ,et al. Twitterrank:finding topic-sensitive influential twitterers[C]// The third ACM international conference on Web search and data mining. 2011: 261-270.
[11]	TANG J , SUN J , WANG C ,et al. Social influence analysis in large-scale network[C]// The 15th ACM SIGKDD international conference on Knowledge discovery and data mining. 2009: 807-816.
[12]	ANTULOV-FANTULIN N , LANCIC A , STEFANCIC H ,et al. Statistical inference framework for source detection of contagion processes on arbitrary network structures[C]// Self-Adaptive and Self-Organizing Systems Workshops (SASOW). 2014: 78-83.
[13]	JIANG J J , WEN S , YU S ,et al. Identifying propagation sources in networks:State-of-the-art and comparative studies[C]// IEEE Communications Surveys ＆ Tutorials. 2016: 165-481
[14]	ALTARELLI F , BRAUNSTEIN A , DALL’ASTA L ,et al. The patient-zero problem with noisy observations[J]. Journal of Statistical Mechanics:Theory and Experiment, 2014(10).

Topic A		Topic B		Topic C
Username	In-degree	Username	In-degree	Username	In-degree
qqent	377	zhangjie	1313	QQGenius	8968
cv13227	69	QQGenius	1168	sky	142
yiren7899	59	pictalks	936	weishi	126
yingzi337	38	xujinglei	652	liu16261	52
huaitu	28	nmoney	595	ph7963	20
yehuo61	24	zr19970	476	chouduo	19
zzc3855	24	QH-6577	352	weiying	8

Username	Pr value	In-degree
qqent	0.053 75	377
cv13227	0.008 83	69
yiren7899	0.005 97	59
dongyang	0.004 15	12
huaitu	0.003 79	28
baiduxxb	0.003 72	23
yingzi337	0.003 62	38
A30783	0.003 13	17
mit49699	0.003 00	23
yehuo61	0.002 93	24

Username	Pr value	In-degree
pictalks	0.02119	936
QQGenius	0.01905	1168
zhangjie	0.01677	1313
xujinglei	0.00729	652
nmoney	0.00534	595
zr19970	0.00512	476
zhangyue	0.00333	241
QH-6577	0.00299	352
shouji129	0.00290	343
shoujiya	0.00233	348

Username	Pr value	In-degree
QQGeniuss	0.157 44	8968
liu16261	0.126 50	52
weishi	0.002 80	126
sky	0.001 78	142
chouduo	0.000 27	19
ph7963	0.000 21	20
hashidayin	0.000 15	7
q23002	0.000 11	7
weiying	0.000 11	8
caozhuhua	0.000 10	5

Topic	Accuracy
Topic A	1.0
Topic B	1.0
Topic C	0.64

Information tracing model based on PageRank

在线阅读

pdf下载

可视化

摘要/Abstract

引用本文

使用本文

图/表 11

参考文献 14

相关文章 0

Metrics

推荐阅读 0