Big Data Research On The Characteristics And Revolution Of Railway Passenger Social Networks

In the study of passenger travel characteristics,most of the passengers are regarded as independent individuals,and the co-travel behavior is often overlooked.However,in the process of co-travel,the behavioral preferences of passengers are often influenced by their peers.Therefore,the study of co-travel patterns is a new perspective of passenger characteristics research.In order to better understand the characteristics of railway travelers' behavior,this paper proposes a method of extracting passenger relations based on research methods of social networks,builds a model of passenger social networks,and extracts passengers' co-travel behavior based on the railway passenger ticket data during the Spring Rush,building a railway passenger social network.Based on the railway passenger ticket data during Spring Festival,this paper extracts the relationships of co-travel passengers and constructs the railway co-travel passenger networks by social networks methods.This paper also analyzes the basic characteristics of railway co-travel passenger networks,and discusses the co-travel characteristics of passengers at different gender and different ages.The differences between civil aviation co-travel passenger networks and railway co-travel passenger networks are also analyzed.The empirical results show that during Spring Festival,railway co-travel passenger networks has the characteristics of low density,large number of partitions,and low average weight of edges.Comparing with the civil aviation co-travel passenger networks,it has larger number of nodes,larger diameter and smaller network density.In the analysis of the static characteristics of the railway passenger co-travel network,this paper finds that there are significant differences in the distribution of railway passengers of different ages across different scales of subnets.Young people are the subject of common co-travel passengers.At the same time,young people are also biased to travel in smaller groups.In addition,this paper analyzes the importance of nodes and community modularity of the largest subnet,and finds that the closeness of nodes in communities is higher than that of the overall connected subnet,and the association between communities is sparse.Finally,this paper analyzes the evolution characteristics of connected subnets of different scales,and analyzes the time characteristics of the co-travel behaviors of Spring Festival travelers.In summary,based on the railway passenger peer network,this paper analyzes the static characteristics and dynamic characteristics of travelers' co-travel behavior which can help transport and travel departments and related enterprises to improve management and service quality.