Evolution of Friendship: a case study of MobiClique

被引:7
作者
Lee, JooYoung [1 ]
Lopatin, Kontantin [2 ]
Hussain, Rasheed [3 ]
Nawaz, Waqas [4 ]
机构
[1] Innopolis Univ, Network Sci & Informat Lab, Inst Informat Syst, Innopolis, Russia
[2] Innopolis Univ, Innopolis, Russia
[3] Innopolis Univ, Inst Informat Syst, Innopolis, Russia
[4] Islamic Univ Medina, Coll Comp & Informat Syst, Medina, Saudi Arabia
来源
ACM INTERNATIONAL CONFERENCE ON COMPUTING FRONTIERS 2017 | 2017年
关键词
social network anlaysis; community detection; link prediction;
D O I
10.1145/3075564.3075595
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Understanding the evolution of relationship among users, through generic interactions, is the key driving force to this study. We model the evolution of friendship in the social network of MobiClique using observations of interactions among users. MobiClique is a mobile ad-hoc network setting where Bluetooth enabled mobile devices communicate directly with each other as they meet opportunistically. We first apply existing topological methods to predict future friendship in MobiClique and then compare the results with the proposed interaction-based method. Our approach combines four types of user activity information to measure the similarity between users at any specific time. We also define the temporal accuracy evaluation metric and show that interaction data with temporal information is a good indicator to predict temporal social ties. The experimental evaluation suggests that the well-known static topological metrics do not perform well in ad-hoc network scenario. The results suggest that to accurately predict evolution of friendship, or topology of the network, it is necessary to utilise some interaction information.
引用
收藏
页码:267 / 270
页数:4
相关论文
共 8 条
[1]  
[Anonymous], 2006, P SDM 06 WORKSH LINK
[2]   Time Frame based Link Prediction in Directed Citation Networks [J].
Jawed, Mujtaba ;
Kaya, Mehmet ;
Alhajj, Reda .
PROCEEDINGS OF THE 2015 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM 2015), 2015, :1162-1168
[3]  
Pietiläinen AK, 2009, 2ND ACM SIGCOMM WORKSHOP ON ONLINE SOCIAL NETWORKS (WOSN 09), P49
[4]  
Pietilainen A-K, 2009, WOSN 09
[5]  
Taskar B, 2004, ADV NEUR IN, V16, P659
[6]   Location Prediction via Social Contents and Behaviors: Location-aware Behavioral LDA [J].
Tigunova, Anna ;
Lee, JooYoung ;
Nobari, Sadegh .
2015 IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOP (ICDMW), 2015, :1131-1135
[7]   Link prediction in social networks: the state-of-the-art [J].
Wang Peng ;
Xu BaoWen ;
Wu YuRong ;
Zhou XiaoYu .
SCIENCE CHINA-INFORMATION SCIENCES, 2015, 58 (01) :1-38
[8]   An Approach to Cold-Start Link Prediction: Establishing Connections between Non-Topological and Topological Information [J].
Wang, Zhiqiang ;
Liang, Jiye ;
Li, Ru ;
Qian, Yuhua .
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2016, 28 (11) :2857-2870