Study On The Measurement Of The Impact Of Extreme Weather On The Public Based On Social Media Data

In the process of the gradual development of economy and society,cities,as the main centers of population and economic activities,are most prone to various natural disasters,such as rainstorm and other extreme weather threats.These natural disasters have had a negative impact on people,transport,public services and business in cities.As the principal part of urban governance,the urban public is crucial to urban development.The continuous promotion of the people-centered governance concept requires that more consideration be given to the role of the urban public in improving urban construction.In emergency and disaster management,the analysis of public behavior and impact is crucial to plan formulation and construction improvement.Therefore,a quick grasp of the impact of rainstorm events on the city and the urban public is an important way to understand the resilience of cities and enhance their resilience.This paper takes the impact of extreme weather on urban public as the research object.First,on the basis of literature reading and case studies,it systematically sorts out urban disasters and disaster research and management methods,introduces public impact measurement and evaluation indicators and conducts quantitative research,and adopts multiple analysis methods such as time series analysis and sentiment analysis.Construct and verify the social public impact measurement system under urban disaster.Select practical cases,use Python crawler technology to crawl social media microblogging data,and conduct data analysis and mining of social media data based on data-driven methods.At the same time,public opinion theme modeling analysis was carried out to explore the impact level of heavy rain disaster events on the urban public and put forward targeted urban disaster resilience strategies.The results show that the changes of urban public behavior and emotional influence in time dimension reach their peak during the rainstorm,and the duration is longer,showing a certain lag effect compared with the actual duration of the event.In terms of content dimension,public opinion theme analysis is carried out on social media data,and five categories of clustering results are obtained based on LDA theme modeling analysis.The specific results are as follows: overall description of rainstorm event,weather forecast and traffic impact,social event caused by rainstorm,disaster event caused by rainstorm,daily life and emotional expression.The results show that the urban system has a certain resilience,but the public in the city is deeply affected by the rainstorm disaster,and the impact time is longer.From the perspective of urban public,this study systematically examines the disaster resistance level of Chinese cities under natural disasters,providing a new perspective and method for the study of urban disaster management and social resilience,helping to improve urban resilience,promote social health and equity,and providing references for the communication and cooperation,information exchange and policy formulation among government,social organizations and the public during disasters.