Research On The Spatial-Temporal Law Of Human Mobility Based On Social Media

Human activities affect the transportation,housing,business,culture,infrastructure and other aspects of urban development and related aspects,understanding of human activities contribute to the city's planning and construction.In recent years,the development of a location-based social media platform has enabled people's lives to extend from the real world to the virtual world.People are also active in the virtual world in part time in the real world,and the location and time are two bridges of the world,people left the location and time information in the virtual world when they do activities in the real world.We can according to the user in the virtual world to leave time and space information on human behavior in the real world.The vast majority of people in real life have a fixed pace of life,so their activities have a certain law to follow,but because of the complexity of life,people follow the regular activities at the same time also carried out some accidental activities.How to extract regular activities from accidental activities becomes a challenge to study the laws of human activities.Based on the social media data,this paper uses the extended Markov model to study the proportion of human activities and analyzes the impact of group activities on urban population movements.Then,the spatial and temporal path theory is used to extract the main activity patterns of human beings,and the clustering algorithm is used to divide the users into different categories according to the activity pattern.The temporal and spatial characteristics of certain categories are studied.The main work of this paper is as follows:1)Based on the idea of state transition in the Markov model,the time dimension is added to the model to study the possibility of human movement at different positions and in different positions,including human activity extraction,human activity location detection,human activity location transformation detection,integrated prediction algorithm design2)Applying the detection method of individual movement law to the group movement law,the probability of using the activity location reflects the aggregation situation of the urban population at different times,and the probability of using the activity location conversion reflects the flow of the crowd at different times.And use ECharts to dynamically show the dynamics of the population.3)The application of the theory of time-space path to the long-term main activity mode of human exploration,the study of human activities hot spot extraction and clustering methods,space-time path generation and path probability calculation.Using the combination of parameters generated by the user multiple time and space path,access to a more comprehensive user activity mode.The space-time path is displayed in a three-dimensional space with a Z-axis of 24 hours to obtain a change in the law of the movement over time in the day.4)The time and space paths of different users have different temporal and spatial characteristics,representing different modes of activity.The space-time path of different time-space characteristics is divided into different categories to study the time and space rules of different categories of users.