许多重要的经济领域中，信息的传播和交流对于整体经济运行具有重要 意义。社会个体受到信息的影响，不断分析周围人的信息并对其进行学习从 而更新自己的行为。理解社会系统中个体如何学习和决策对于更好的预测， 利用，干预和控制社会中的行为演化有着重要的意义和作用，可以为解决一 些实际的问题提供一些科学的管理策略和支持。 若将社会中的决策个体看作网络中的一个个节点，决策者的社会关系看 作社会网络中的连线，那么可以把整个社会系统抽象为社会网络。本文从社 会网络的角度来研究社会中个体的学习和决策行为，把个体的决策行为区分 为了学习过程和选择过程，分别对两个过程构建模型，并通过信念这个中 间桥梁把两个过程有机地结合在了一起。并通过结合具体的实验数据来和 模型预测进行比对，对数据进行了合理分析和处理，证明了degree weighting 的DeGroot 模型对于网络中的学习和决策有着更好的解释力，并且决策者的 决策时间和对于自己在网络中学习地效果和信念有着重要关系。

In many important economic fields, the dissemination and exchange of information is of great significance to the overall economic situation. Individuals are influenced by information, they analyze the information of people around them and learning those to update their behavior. Understanding how individuals learn and make decisions in the social system has important implications and functions for better prediction, utilization, intervention, and control of society evolution. And it can provide some scientific management strategies and support for solving practical problems.

If the individual in society is regarded as a node in the network and the social relationship of the individual is regarded as a connection in the social network, then the whole social system can be abstracted into a social network. This paper studies the individual decision-making behavior in society from the perspective of social network, and divides the individual decision-making behavior into the learning process and the selection process. It constructs two processes separately and organically combines the two processes through the intermediate bridge of beliefs. By combining the specific experimental data to compare with the model prediction, the data is reasonably analyzed and processed, which proves that the degree weighting DeGroot model has better explanatory power for learning and decision making in the network, and decision time has an important relationship with the effects and beliefs of learning in the network.