| In the context of deepening social awareness of fairness and justice,this paper uses big data analysis as a means to select some parks in Harbin as the analysis object.From the perspective of outcome equity,the fairness of different parks is measured by the dispersion degree of different tourists’ subjective experience in parks.Firstly,data acquisition is carried out by web crawler.Using text analysis methods,including word frequency analysis,new word discovery and text clustering analysis of topic trends;Through emotion analysis,the subjective experience differences of different tourists in the park are transformed into objective data that can be compared.The standard deviation calculation fair comparison,and through the topic trend with tourists emotional characteristics,the correlation between fairness difference contrast,puts forward several factors affecting the fairness of Harbin city park,mainly include: culture and park,the natural scenery and landscape environmental quality and the quality of park management,security,and other factors.Finally,from the design,management of two aspects,Harbin city park put forward suggestions.Based on the differences of users’ needs,this paper makes a comparative analysis of the differences between different visitors’ emotional dispersion degree and fairness of park experience,and innovates the evaluation method of green space fairness from the perspective of outcome fairness.This paper tries to apply social media data to the fairness evaluation of park green space.Compared with traditional questionnaire survey methods,using massive social media data has the characteristics of large amount of data,fast collection,timeliness and authenticity.Future research can explore and analyze a large amount of existing network data and improve the shortcomings of this paper. |
