Input-output relationship in social communications characterized by spike train analysis
Input-output relationship in social communications characterized by spike train analysis
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DOI：
10.1103/physreve.94.042313
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发表时间：
2016-10-24
影响因子：
2.4
通讯作者：
Lambiotte, Renaud
中科院分区：
文献类型：
--
作者：
Aoki, Takaaki;Takaguchi, Taro;Lambiotte, Renaud
我们通过不同的渠道研究人类交流的动态特性，即，短消息、电话和电子邮件，采用来自神经元尖峰序列分析的技术，以表征连续间隔时间的时间波动。我们首先测量所谓的本地变化（LV）的传入和传出的事件序列的用户，并发现这些输入和输出LV值是正相关的短消息和不相关的电话和电子邮件。其次，我们分析了接收消息后的响应时间分布，重点关注这些通道中的输入输出关系。我们发现，三个通道之间的反应的时间尺度和幅度不同。为了了解响应时间分布对LV值之间的相关性的影响，我们开发了一个点过程模型，其活动率由传入和传出事件调制。模型的数值模拟表明，对传入事件的快速反应和传出事件后的不应效应是重现LV正相关的关键因素。
We study the dynamical properties of human communication through different channels, i.e., short messages, phone calls, and emails, adopting techniques from neuronal spike train analysis in order to characterize the temporal fluctuations of successive interevent times. We first measure the so-called local variation (LV) of incoming and outgoing event sequences of users and find that these in-and out-LV values are positively correlated for short messages and uncorrelated for phone calls and emails. Second, we analyze the response-time distribution after receiving a message to focus on the input-output relationship in each of these channels. We find that the time scales and amplitudes of response differ between the three channels. To understand the effects of the response-time distribution on the correlations between the LV values, we develop a point process model whose activity rate is modulated by incoming and outgoing events. Numerical simulations of the model indicate that a quick response to incoming events and a refractory effect after outgoing events are key factors to reproduce the positive LV correlations.