Time Evolution And Comparative Analysis Of Central Characteristics Of Directed Weighted Networks In Mobile Communication Data Between Milan And Trentino,Italy

The rapid development of communication technology has resulted in a huge amount of mobile communication data with location information.By using large data technology to analyze location-based mobile communication data,we can understand the dynamic changes of communication interaction modes between different regions.Analyzing the time evolution law of directional weighted network characteristics in mobile communication data and grasping the periodicity of network characteristics can provide assistant decision-making for dynamic allocation and management optimization of communication resources.This paper presents a time evolution analysis based on the centrality of directed weighted network in mobile communication data,including(1)building directed weighted network from mobile communication data by using Spark large data platform.(2)On the three time scales of month,week and day,Hurst exponents of five network characteristics,namely maximum value,maximum degree of entry,maximum degree of exit,maximum PageRank and freeman,are calculated respectively.(3)The Pearson index is obtained by analyzing the Hurst index on the time scales of month,week and day respectively.(4)The Hurst index and Pearson index of news volume correlation analysis of three time scales in different regions were compared and analyzed.Milan and Turin in Italy were selected as the study areas.The mobile communication data and daily news volume in November 2013 were used as the experimental data.The results show that:(1)The average Hurst index calculated by day in Milan and Turin is higher than the average Hurst index calculated by week and month,which indicates that each characteristic value maintains a stronger periodicity in a shorter time scale.The results calculated by day and week in Milan are similar,and the maximum value can maintain the best periodicity,while PageRank's periodicity is the weakest.It shows that the periodicity of weekly and daily calls of residents in Milan is obvious.In Turin,the center of Freeman network has the strongest periodicity and PageRank has the weakest periodicity.It shows that the daily call aggregation of residents in Turin is relatively stable,but there is no obvious regularity in the intensity of calls in different regions.(2)The Hurst index of each characteristic value of Milan and Turin is positively correlated with the local news volume,and the Hurst index of the maximum value of the two cities is positively correlated with the local news volume,which indicates that the periodicity of the maximum daily call volume of the two cities has a strong correlation with the news volume of the two cities in themonth.