Quantitative Analysis On The Statistical Properties Of Historical Figures And Historical Events

Complex network and time series analysis are two important methods in sta-tistical physics,they have been used to study the characteristics of individuals in complex systems,and the properties of the interactions among individuals.Quanti-tative analysis of human social relations and human behavior dynamics is one of the important frontier topics in the field of complex systems.In this thesis,the quan-titative statistics of a large number of historical events in the Spring and Autumn Period and the Warring States Period in China have been collected and processed,quantitative studies on the statistical regularities of historical figures and historical events have been carried out by using the metrics of complex network and time series analysis.The main contents and results are as follows:1.Construction of the historical characters' relationship network and analysis of its topological properties.It is found that the historical characters' relationship net-work has two common characteristics,namely the scale-free characteristic expressed by power-law degree distribution and the small-world characteristic described by a short path length.In the mean time,the network has homology and a good hierar-chical relation.Using the community detection algorithm,it is found that historical figures in the same period of the network normally appear in the same community.In the Spring and Autumn Period,the more connected nodes in the communities are kings and doctors,while in the Warring States period they are monarchs and soldiers.This shows that the Spring and Autumn Period tends to reconcile but the Warring States Period tends to be in the war.2.Mining of the important historical figures and important historical events.Using the key node mining algorithms in complex networks,the important historical figures and important historical events are quantitatively analyzed.By comparing the different algorithms,it is found that the local centrality algorithm is a better way to detect the important characteristics of historical figures.At the same time,using the rankings of important historical figures,and combining with the number of participants in the events,the importance quantities of historical events are proposed,and then the important historical events are excavated.3.Studies on the statistical characteristics of historical figures and historical events.Results show that the time intervals for historical figures to participate in historical events obey the power law characteristic,and the evolution of the number of historical events and the number of persons participating in historical events over time satisfies the Heaps law,The frequency of historical figures participating in historical events satisfies the Zipf law.By analyzing the correlation between the importance of characters and the frequency,as well as the time interval of characters participating in events,it is found that the importance of characters correlates more strongly with the frequency of characters participating in events.