Analysis On Residents' Spatiotemporal Behaviors Based On Weibo Data

With the rapid development of economic development and information technology,there are more and more researches on big data,especially the demand for spatial data is the most intense,and the social media geographical data in these spatial data has an important influence and role.Many scholars have analyzed these data to obtain the desired results.In these studies,the spatial and temporal behavior of urban residents and the distribution of urban functional areas,that is,the discovery of hotspots,played a major role in the planning of cities and the needs of residents..Since Weibo users are representative of the overall resident users,this paper obtains Sina Weibo's check-in data through webpage crawling technology,and in combination with other data,explores hotspot areas in Beijing and conducts research on the temporal and spatial behavior characteristics of Beijing residents.The specific research contents of these issues are as follows:(1)Network data collection and preprocessing.The web crawler crawls Sina Weibo's check-in data by focusing on the web crawler,and then processes the data that has been crawled.Preprocessing includes the removal of redundant data and the reclassification of POIs of interest points,and then compares Beijing POI sample data.We verify the correctness of the data we have obtained with the distribution of the microblogging check-in data in Beijing.(2)The discovery of hotspots in Beijing based on nuclear density analysis.Firstly,the urban functional areas in Beijing were divided through the distribution map of Beijing POI sample data in Beijing,and then the thermal analysis of Beijing was conducted through a spatial analysis method based on nuclear density analysis.Through the heat map display,the work of Beijing was finally found out.The hotspots of the three functional areas of the office area,commercial consumption area,and residential space area.(3)Spatial-temporal clustering-based characteristics of space-time behavior of Beijing residents' commuting and leisure activities.In terms of time,we analyze the number of microblogs in each time period during the day,and further understand the urban functional areas.In terms of space,we visualize the data of each time period in Beijing,and discover Beijing through the urban heat map.The characteristics of residents' spatial behavior,and finally concluded the relationship between residents' travel and the distribution of urban functional areas.