Human comment dynamics in on-line social systems
Human comment dynamics in on-line social systems
复制标题
在线社交系统中的人类评论动态
DOI：
10.1016/j.physa.2010.08.049
复制
发表时间：
2010-12-15
影响因子：
3.3
通讯作者：
Kurths, Juergen
中科院分区：
文献类型：
--
作者：
Wu, Ye;Zhou, Changsong;Kurths, Juergen
本文使用中国最受欢迎的在线社交系统“天涯”上的数据来研究人的评论。我们发现，同一话题的两个连续评论之间的时间间隔，称为事件间时间，服从幂规律分布。这一结果表明，主题不存在特征衰减时间。它允许很长一段时间没有评论，从而将密集的评论分开。此外，不同的ID对同一话题发表评论的频率也遵循指数分布。这表明，在话题中存在着一些引领舆论方向的“枢纽”。基于个人的评论习惯，我们引入了一个模型来解释这些现象。模型的数值模拟结果与实验结果吻合较好。我们的发现有助于发现人类在网络社会中的行为规律，以及虚拟社会和现实社会舆论的演变。(C)2010爱思唯尔B.V.保留所有权利。
Human comment is studied using data from 'tianya' which is one of the most popular on-line social systems in China. We found that the time interval between two consecutive comments on the same topic, called inter-event time, follows a power-law distribution. This result shows that there is no characteristic decay time on a topic. It allows for very long periods without comments that separate bursts of intensive comments. Furthermore, the frequency of a different ID commenting on a topic also follows a power-law distribution. It indicates that there are some "hubs" in the topic who lead the direction of the public opinion. Based on the personal comments habit, a model is introduced to explain these phenomena. The numerical simulations of the model fit well with the empirical results. Our findings are helpful for discovering regular patterns of human behavior in on-line society and the evolution of the public opinion on the virtual as well as real society. (c) 2010 Elsevier B.V. All rights reserved.