Study On Satisfaction Of "PingAn Good Doctors" APP Based On Text Mining

With the advent of the Mobile Internet era,a wide variety of APP related to people's livelihood have emerged.Relying on the Internet platform with high transparency and high engagement,there are lots of online medical APP providing cheaper and more convenient medical service for the masses.As a representative of mobile online medical products,“PingAn Good Doctor” breaks through the limitation of time and space,and it is extremely convenient to meet the medical and health needs of customers.However,due to the late start of mobile online medical treatment in China,the market development in this field is not mature.And the problems caused by insufficient internal economic interests,non-standard information management protection and obvious product homogeneity still make the development of this field face severe challenges.In this realistic context,there is more practical significance studying the actual needs of users using mobile medical products and the factors affecting their satisfaction for the long-term development of mobile medical products.Taking the “PingAn Good Doctor” APP as an example,some research on this issue is carried out using the method of text mining in this paper.Firstly,the comment text about “PingAn Good Doctor” APP is grabbed from the “pea pod”,“YingYongBao” and itunes.Meanwhile,the word segmentation tools “JieBa” is improved based on this data.Secondly,the analysis about textual features is made on the crawled comment data,getting the corresponding word cloud graph and network semantic graph.From such an analysis,the high-frequency words and the evaluation words associated with it are obtained.The users' satisfaction with the experience of “PingAn Good Doctor” APP is showed from different dimensions.The keywords are extracted using improved TextRank algorithm based on Word2 Vec,getting the factors affecting users' satisfaction.Finally,on the basis of the performance of textual features,the affective word pairs of the comment are extracted according to the POS template,And the affective values of the features are calculated applying the dictionary method.The comprehensive evaluation of “PingAn Good Doctor” APP users' satisfaction is obtained.Furthermore,some corresponding countermeasures and suggestions are analyzed.The results show that,firstly,some factors like “health management”,“online consultation”,“functional service” and “platform activities” are more important in the user experience of “PingAn Good Doctors” APP.According to our text analysis results,“online clinic” is the most important factor for users,indicating that convenient treatment is still the potential maximum demand of users.Secondly,in terms of the comprehensive evaluation result of satisfaction,the products of “PingAn Good Doctor” APP are positively recognized by users,with the overall satisfaction reaching 71.99%.And there are also high levels of satisfaction with each sub-dimension,especially the satisfaction of “health function” reaches 80%.Thirdly,for APP developers and operators online,they should ensure that the functional needs of users are met.At the same time,they should pay much attention to the completeness of service itself.The user's satisfaction will be increased by improving the interactive experience of functional design and page design.