Uncovering offline event similarity of online friends by constructing null models

论文摘要

The emergence of Event-based Social Network（EBSN） data that contain both social and event information has cleared the way to study the social interactive relationship between the virtual interactions and physical interactions. In existing studies, it is not really clear which factors affect event similarity between online friends and the influence degree of each factor. In this study, a multi-layer network based on the Plancast service data is constructed. The the user’s events belongingness is shuffled by constructing two null models to detect offline event similarity between online friends. The results indicate that there is a strong correlation between online social proximity and offline event similarity. The micro-scale structures at multi-levels of the Plancast online social network are also maintained by constructing 0 k–3 k null models to study how the micro-scale characteristics of online networks affect the similarity of offline events. It is found that the assortativity pattern is a significant micro-scale characteristic to maintain offline event similarity. Finally, we study how structural diversity of online friends affects the offline event similarity. We find that the subgraph structure of common friends has no positive impact on event similarity while the number of common friends plays a key role, which is different from other studies. In addition, we discuss the randomness of different null models, which can measure the degree of information availability in privacy protection. Our study not only uncovers the factors that affect offline event similarity between friends but also presents a framework for understanding the pattern of human mobility.

论文目录

• 1.Introduction
• 2. Detecting offline event similarity in Plancast
•   2.1. Constructing the multi-layer Plancast network
•   2.2. Indexes to measure offline event similarity
•   2.3. Null models of exchanging trajectory
•   2.4. Null models of exchanging user events
•   2.5. Offline event similarity between friends
• 3. The impact of online subgraph structures on offline event similarity
•   3.1.0k null network of EBSN
•   3.2.1k null networks of EBSN
•   3.3.2k null network of EBSN
•   3.4.3k null network of EBSN
•   3.5. The impact of online social micro-scale structures on offline event similarity
• 4. The impact of structural diversity of online friends on offline event similarity
•   4.1. Indexes to measure online structural diversity
•   4.2. The impact of the number of common neighbors
•   4.3. The impact of the subgraph structure of common neighbors
•   4.4. Randomness of offline event similarity
• 5. Conclusion

文章来源

类型: 期刊论文

作者: 崔文阔,肖婧,李婷,许小可

来源: Chinese Physics B 2019年06期

年度: 2019

分类: 基础科学

专业: 数学

单位: College of Information and Communication Engineering, Dalian Minzu University,Guizhou Provincial Key Laboratory of Public Big Data, Guizhou University

基金: Project supported by the National Natural Science Foundation of China(Grant Nos.61773091,61603073,61601081,and 61501107),the Natural Science Foundation of Liaoning Province,China(Grant No.201602200)

分类号: O157.5

页码: 486-494

总页数: 9

文件大小: 741K

下载量: 28