NDLI: Mining friendships through spatial-temporal features in mobile social networks

Content Provider	IEEE Xplore Digital Library
Author	Jianwei Niu Danning Wang Jie Lu
Copyright Year	2015
Description	Author affiliation: State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering, Beihang University, Beijing 100191, China (Jianwei Niu; Danning Wang; Jie Lu)
Abstract	With the rapid popularization of smartphones and tablets, there are thousands of applications based on mobile social networks. The big data from these networks provide a huge potential to shed light on the mobility patterns of users. These big data enable a deeper understanding of users' preferences and behaviors and will help us mine users' friendship in both physical and digital worlds. In this paper, we firstly divide user mobility patterns into different categories to portray the characteristics of user encounter more precisely. Then, with combining proximity data from bluetooth devices and location data from cellular towers, we introduce a set of spatial-temporal features, including the encounter entropy, which measures the probability of encounters between different mobile users. Using these spatial-temporal features, we provide a novel model to infer user friendship by analyzing the social context of users and their encounters. To address the class imbalance problem in the dataset and improve the prediction accuracy of friendship, we employ the sampling method and evaluate our model with three different classifiers. The experimental results show that our encounter entropy feature has a striking effect to infer user friendship, and our model based on these spatial-temporal features can achieve pretty good accuracy in predicting friendship over real human mobility traces without privacy-sensitive information disclosure.
Starting Page	1
Ending Page	8
File Size	243562
Page Count	8
File Format	PDF
ISSN	23749628
e-ISBN	9781467385909
DOI	10.1109/PCCC.2015.7410269
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-12-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Poles and towers Bluetooth Social network services Entropy Smart phones Mobile communication spatial-temporal features mobile social networks friendship inferring proximity and location data
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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