论文标题
时间网络认识论：在现实世界中达成共识时
Temporal Network Epistemology: on Reaching Consensus in Real World Setting
论文作者
论文摘要
这项工作开发了时间网络认识论模型的概念，从而可以在动态网络中对学习过程进行模拟。该研究的结果是在使用COGSNET模型和静态拓扑结构产生的时间社交网络上进行的，这表明网络时间动态对学习过程的结果和流动的重要影响。已经表明，与基线模型相比，达成共识的动力学不仅不同，而且还出现了以前未观察到的现象，例如未知的药物或针对分离的组件的不同共识状态。还观察到，有时只有网络结构的变化才能有助于达成共识。引入的方法和实验结果可以用来更好地理解人类社区在科学层面上共同解决复杂问题的方式，并询问较不复杂但普遍且同样重要的信念在整个社会中传播的正确性。
This work develops the concept of temporal network epistemology model enabling the simulation of the learning process in dynamic networks. The results of the research, conducted on the temporal social network generated using the CogSNet model and on the static topologies as a reference, indicate a significant influence of the network temporal dynamics on the outcome and flow of the learning process. It has been shown that not only the dynamics of reaching consensus is different compared to baseline models but also that previously unobserved phenomena appear, such as uninformed agents or different consensus states for disconnected components. It has been also observed that sometimes only the change of the network structure can contribute to reaching consensus. The introduced approach and the experimental results can be used to better understand the way how human communities collectively solve both complex problems at the scientific level and to inquire into the correctness of less complex but common and equally important beliefs' spreading across entire societies.
