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Inferring and analysis of social networks using RFID check-in data in China

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成果类型:
期刊论文
作者:
Liu, Tao;Yang, Lintao*;Liu, Shouyin;Ge, Shuangkui
通讯作者:
Yang, Lintao
作者机构:
[Liu, Shouyin; Liu, Tao; Yang, Lintao] Cent China Normal Univ, Coll Phys Sci & Technol, Wuhan, Hubei Province, Peoples R China.
[Liu, Tao] Jiujiang Univ, Sch Informat Sci & Technol, Jiujiang, Jiangxi, Peoples R China.
[Liu, Shouyin; Liu, Tao; Yang, Lintao] Cent China Normal Univ, Collaborat & Innovat Ctr Educ Technol, Wuhan, Hubei Province, Peoples R China.
[Ge, Shuangkui] Beijing Inst Elect Technol & Applicat, Beijing, Peoples R China.
通讯机构:
[Yang, Lintao] C
Cent China Normal Univ, Coll Phys Sci & Technol, Wuhan, Hubei Province, Peoples R China.
Cent China Normal Univ, Collaborat & Innovat Ctr Educ Technol, Wuhan, Hubei Province, Peoples R China.
语种:
英文
关键词:
Schools;Social networks;Community structure;Undergraduates;China;Distribution curves;Communications;Social communication
期刊:
PLOS ONE
ISSN:
1932-6203
年:
2017
卷:
12
期:
6
页码:
e0178492
基金类别:
MOEMinistry of Education, SingaporeMinistry of Higher Education & Scientific Research (MHESR) [ccnu16JYI00019, CCNU17QN0011]
机构署名:
本校为第一且通讯机构
院系归属:
物理科学与技术学院
摘要:
Social networks play an important role in our daily lives. However, social ties are rather elusive to quantify, especially for large groups of subjects over prolonged periods of time. In this work, we first propose a methodology for extracting social ties from long spatio-temporal data streams, where the subjects are 17,795 undergraduates from a university of China and the data streams are the 9,147,106 time-stamped RFID check-in records left behind by them during one academic year. By several metrics mentioned below, we then analyze the struct...

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