Department of Biomedical Engineering and Computational Science, Aalto University School of Science, FI-00076, Espoo, Finland.
Proc Natl Acad Sci U S A. 2013 Nov 5;110(45):18070-5. doi: 10.1073/pnas.1307941110. Epub 2013 Oct 21.
Recent studies on electronic communication records have shown that human communication has complex temporal structure. We study how communication patterns that involve multiple individuals are affected by attributes such as sex and age. To this end, we represent the communication records as a colored temporal network where node color is used to represent individuals' attributes, and identify patterns known as temporal motifs. We then construct a null model for the occurrence of temporal motifs that takes into account the interaction frequencies and connectivity between nodes of different colors. This null model allows us to detect significant patterns in call sequences that cannot be observed in a static network that uses interaction frequencies as link weights. We find sex-related differences in communication patterns in a large dataset of mobile phone records and show the existence of temporal homophily, the tendency of similar individuals to participate in communication patterns beyond what would be expected on the basis of their average interaction frequencies. We also show that temporal patterns differ between dense and sparse neighborhoods in the network. Because also this result is independent of interaction frequencies, it can be seen as an extension of Granovetter's hypothesis to temporal networks.
最近关于电子通信记录的研究表明,人类通信具有复杂的时间结构。我们研究涉及多个个体的通信模式如何受到性别和年龄等属性的影响。为此,我们将通信记录表示为一个彩色时间网络,其中节点颜色用于表示个体的属性,并识别出称为时间模式的模式。然后,我们构建了一个时间模式发生的 null 模型,该模型考虑了不同颜色节点之间的交互频率和连接性。这个 null 模型允许我们在使用交互频率作为链接权重的静态网络中检测到无法观察到的显著呼叫序列模式。我们在一个大型手机记录数据集发现了与性别相关的通信模式差异,并显示了时间同质性的存在,即相似个体参与通信模式的倾向超出了基于其平均交互频率的预期。我们还表明,网络中的密集和稀疏邻域之间存在时间模式差异。由于这个结果也独立于交互频率,因此可以将其视为 Granovetter 假设向时间网络的扩展。