School of Biology and Centre for Social Learning and Cognitive Evolution, University of St. Andrews, Scotland, United Kingdom.
Am J Primatol. 2011 Aug;73(8):834-44. doi: 10.1002/ajp.20920. Epub 2011 Jan 18.
Controversy over claims of cultures in nonhuman primates and other animals has led to a call for quantitative methods that are able to infer social learning from freely interacting groups of animals. Network-based diffusion analysis (NBDA) is such a method that infers social transmission of a behavioral trait when the pattern of acquisition follows the social network. As, relative to other animals, primates may be unusual in their heavy reliance on social learning, with learning frequently directed along pathways of association; in this study, we draw attention to the significance of this method for primatologists. We provide a "users guide" to NBDA methodology, discussing the choice of NBDA model and social network, and suggest model selection procedures. We also present the results of simulations that suggest that NBDA works well even when the assumptions of the underlying model are violated.
关于非人类灵长类动物和其他动物的文化的说法引起了争议，这导致人们呼吁采用能够从自由互动的动物群体中推断出社会学习的定量方法。基于网络的扩散分析 (NBDA) 就是这样一种方法，当获取模式遵循社交网络时，它可以推断出行为特征的社会传播。因为相对于其他动物，灵长类动物可能在很大程度上依赖于社会学习，并且学习通常沿着关联途径进行；在这项研究中，我们提请注意这种方法对灵长类动物学家的重要性。我们提供了 NBDA 方法的“用户指南”，讨论了 NBDA 模型和社交网络的选择，并提出了模型选择程序。我们还展示了模拟结果，表明即使违反了基础模型的假设，NBDA 也能很好地工作。
