School of Biology, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, UK
Philos Trans R Soc Lond B Biol Sci. 2017 Dec 5;372(1735). doi: 10.1098/rstb.2016.0418.
Network-based diffusion analysis (NBDA) is a statistical technique for detecting the social transmission of behavioural innovations in groups of animals, including humans. The strength of social transmission is inferred from the extent to which the diffusion (spread) of the innovation follows a social network. NBDA can have two goals: (a) to establish whether social transmission is occurring and how strong its effects are; and/or (b) to establish the typical pathways of information transfer. The technique has been used in a range of taxa, including primates, cetaceans, birds and fish, using a range of different types of network. Here I investigate the conceptual underpinnings of NBDA, in order to establish the meaning of results using different networks. I develop a model of the social transmission process where each individual observation of the target behaviour affects the rate at which the observer learns that behaviour. I then establish how NBDAs using different networks relate to this underlying process, and thus how we can interpret the results of each. My analysis shows that a different network or networks are appropriate depending on the specific goal or goals of the study, and establishes how the parameter estimates yielded from an NBDA can be interpreted for different networks.This article is part of the themed issue 'Process and pattern in innovations from cells to societies'.
基于网络的扩散分析（NBDA）是一种用于检测动物群体（包括人类）中行为创新社会传播的统计技术。社会传播的强度是根据创新的扩散（传播）在多大程度上遵循社会网络来推断的。NBDA 可以有两个目标：（a）确定社会传播是否发生以及其影响的强度；和/或（b）确定信息传递的典型途径。该技术已在包括灵长类动物、鲸目动物、鸟类和鱼类在内的一系列分类单元中使用，使用了多种不同类型的网络。在这里，我研究了 NBDA 的概念基础，以便使用不同的网络来确定结果的含义。我开发了一个社会传播过程的模型，其中目标行为的每个个体观察都会影响观察者学习该行为的速度。然后，我确定了使用不同网络的 NBDAs 如何与这一基本过程相关，以及我们如何解释每种方法的结果。我的分析表明，根据研究的具体目标或目标，需要使用不同的网络或网络，并且确定了如何解释 NBDA 产生的参数估计值适用于不同的网络。本文是主题为“从细胞到社会的创新过程和模式”的一部分。
