| With the popularization of the mobile Internet and the development of online public welfare platforms,medical crowdfunding has become an important part of the current implementation of charity assistance and health poverty alleviation.Although my country has gradually realized the medical service system of universal medical insurance,the proportion of national self-payment in medical expenditure is still relatively high.In particular,due to the existence of a series of structural and regional problems such as limited medical resources,unbalanced resource allocation,and differences in urban and rural public medical systems,my country is still one of the countries with the highest incidence of catastrophic medical expenditures.Online medical crowdfunding,as a new online financing model,has gradually evolved into an important financing channel for individuals or groups to solve medical and health needs and cope with the huge family medical expenditure.However,the current success rate of medical crowdfunding projects is not high,and there is a large gap in funding capabilities between projects.It is still difficult for fundraisers who are in medical difficulties trying to obtain sufficient donations through medical crowdfunding.Therefore,by digging out the text characteristics of medical crowdfunding projects,trying to explore the important factors of online medical crowdfunding project financing results,and discovering the key strategies to promote the success of medical crowdfunding projects,it is of great significance to promote the healthy development of the medical crowdfunding industry.To this end,based on theories and methods such as text mining,regression analysis,and predictive modeling,this article mines the text characteristics of online medical crowdfunding projects,and summarizes the impact of medical crowdfunding from the perspectives of fundraisers,project texts,and crowdfunding platforms.Based on the signal theory,build a theoretical framework of influencing factors from the three perspectives of project quality signals,fundraiser signals,and disease signals,and explore the influence mechanism of different factors on the results of medical crowdfunding;Then based on different machine learning algorithms to sort and model the importance of factors to determine the optimal model that affects the financing results;finally,from the perspective of project design,platform specification,industry development,and policy implementation,countermeasures and measures to promote the success of medical crowdfunding and industry development are proposed.The thesis work was supported by the National Natural Science Foundation of China’s general project "Research on the Operation and Management Mechanism of Public Science Projects Based on Scientific Research Crowdsourcing Model"(71774083).The specific research is as follows:First,define the related concepts of crowdfunding and medical crowdfunding,sort out the influencing factors of online medical crowdfunding from the perspectives of donors,fundraisers,platforms,projects,etc.,summarize the existing moral and ethical issues in medical crowdfunding,and provide theoretical basis for follow-up research.Subsequently,signal theory was introduced to construct a theoretical model of medical crowdfunding project financing,and research hypotheses were proposed on the basis of theoretical analysis.Through text analysis,descriptive statistics,collinearity test,OLS regression,robustness test,etc.,important influencing factors,identify important influencing factors and their impact mechanism on crowdfunding results;Then,based on models such as MLP neural network,support vector machine,random forest,etc.,the importance of the factors influencing the financing results is ranked,and the optimal model is determined through comparison between models,and the importance of each factor is analyzed.Finally,based on relevant research findings,countermeasures and suggestions to promote the success of medical crowdfunding and the healthy development of the industry are proposed from the perspectives of project design,platform specification,industry development,and policy implementation. |