Empirical analysis of online human dynamics

被引:57
作者
Zhao, Zhi-Dan [1 ]
Zhou, Tao [1 ,2 ]
机构
[1] Univ Elect Sci & Technol China, Web Sci Ctr, Sch Comp Sci & Engn, Chengdu 610054, Peoples R China
[2] Univ Sci & Technol China, Dept Modern Phys, Hefei 230026, Peoples R China
基金
中国国家自然科学基金;
关键词
Human dynamics; Power-law distribution; Activity; Interevent time distribution; CORRESPONDENCE PATTERNS; INTERTRADE DURATIONS; IMPACT; BURSTS; MEMORY;
D O I
10.1016/j.physa.2012.01.008
中图分类号
O4 [物理学];
学科分类号
070305 [高分子化学与物理];
摘要
Patterns of human activities have attracted increasing academic interests, since the quantitative understanding of human behavior is helpful to uncover the origins of many socioeconomic phenomena. This paper focuses on behaviors of Internet users. Six large-scale systems are studied in our experiments, including the movie-watching in Netflix and MovieLens, the transaction in Ebay, the bookmark-collecting in Delicious, and the posting in FreindFeed and Twitter. Empirical analysis reveals some common statistical features of online human behavior: (1) The total number of user's actions, the user's activity, and the interevent time all follow heavy-tailed distributions. (2) There exists a strongly positive correlation between user's activity and the total number of user's actions, and a significantly negative correlation between the user's activity and the width of the interevent time distribution. We further study the rescaling method and show that this method could to some extent eliminate the different statistics among users caused by the different activities, yet the effectiveness depends on the data sets. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:3308 / 3315
页数:8
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