文献类型：期刊文献

英文题名：Calling patterns in human communication dynamics

作者：Jiang, Zhi-Qiang[1,2];Xie, Wen-Jie[1,2];Li, Ming-Xia[1,2];Podobnik, Boris[3,4,5,6];Zhou, Wei-Xing[1,2];Stanley, H. Eugene[3,4]

机构：[1]E China Univ Sci & Technol, Sch Sci, Sch Business, Shanghai 200237, Peoples R China;[2]E China Univ Sci & Technol, Res Ctr Econophys, Shanghai 200237, Peoples R China;[3]Boston Univ, Dept Phys, Boston, MA 02215 USA;[4]Boston Univ, Ctr Polymer Studies, Boston, MA 02215 USA;[5]Zagreb Sch Econ & Management, Zagreb 10000, Croatia;[6]Univ Rijeka, Fac Civil Engn, Rijeka 51000, Croatia

年份：2013

卷号：110

期号：5

起止页码：1600

外文期刊名：PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000314558100014)】；

基金：Z.-Q.J., M.-X.L., and W.-X.Z. received support from the National Natural Science Foundation of China Grant 11205057, the Humanities and Social Sciences Fund (Ministry of Education of China Grant 09YJCZH040), and Fok Ying Tong Education Foundation Grant 132013. B.P. and H.E.S. received support from the Defense Threat Reduction Agency (DTRA), the Office of Naval Research (ONR), and the National Science Foundation (NSF) Grant CMMI 1125290.

语种：英文

外文关键词：human dynamics; phone user categorization; social science; nonlinear dynamics; social networks

摘要：Modern technologies not only provide a variety of communication modes (e.g., texting, cell phone conversation, and online instant messaging), but also detailed electronic traces of these communications between individuals. These electronic traces indicate that the interactions occur in temporal bursts. Here, we study intercall duration of communications of the 100,000 most active cell phone users of a Chinese mobile phone operator. We confirm that the intercall durations follow a power-law distribution with an exponential cutoff at the population level but find differences when focusing on individual users. We apply statistical tests at the individual level and find that the intercall durations follow a power-law distribution for only 3,460 individuals (3.46%). The intercall durations for the majority (73.34%) follow a Weibull distribution. We quantify individual users using three measures: out-degree, percentage of outgoing calls, and communication diversity. We find that the cell phone users with a power-law duration distribution fall into three anomalous clusters: robot-based callers, telecom fraud, and telephone sales. This information is of interest to both academics and practitioners, mobile telecom operators in particular. In contrast, the individual users with a Weibull duration distribution form the fourth cluster of ordinary cell phone users. We also discover more information about the calling patterns of these four clusters (e.g., the probability that a user will call the c(r)-th most contact and the probability distribution of burst sizes). Our findings may enable a more detailed analysis of the huge body of data contained in the logs of massive users.