情报科学 ›› 2022, Vol. 40 ›› Issue (5): 118-127.

• 业务研究 • 上一篇    下一篇

基于支付意愿的数字阅读用户画像聚类研究 

  

  • 出版日期:2022-05-01 发布日期:2022-05-30

  • Online:2022-05-01 Published:2022-05-30

摘要: 【目的/意义】随着数字阅读版权化的逐步加深,付费用户的比例大幅增加,从用户支付意愿视角切入,构建
不同类型的数字阅读用户画像,并探究影响其支付行为的影响因素。【方法
/过程】通过问卷和采访的形式对受访对
象进行调查,使用
K-Means聚类方法对数字阅读用户的阅读习惯及支付意愿进行数据挖掘,构建不同的用户画像,
对每类数字阅读用户画像的特点进行分析,总结影响各类用户进行付费数字阅读的因素。【结果
/结论】归纳出五类
用户画像,即
A类经济型用户、B类编辑型用户、C类交流型用户、D类沉默型用户、E类放松型用户,在形式创新、内
容优化等方面为各类数字阅读平台未来发展提供一定的参考价值。【创新
/局限】挖掘出每类用户支付行为的影响
因素,同时指出同一用户在不同时期呈现出不同的用户画像。在后续的研究中,将通过收集更大量且具体的客观
数据资料,来进一步完善数字阅读用户画像的研究。

Abstract:

Purpose/significanceWith the gradual deepening of digital reading copyright,the proportion of users paying has increased significantly.From the perspective of users' willingness to pay,this paper constructs several different types of digital reading user por⁃traits.and explores the influencing factors of their payment behavior. Method/processThrough questionnaire and interview to survey respondents.this paper uses K-Means clustering method to dig user's reading habits and willingness,builds different users portraits,an⁃alyzes the characteristics of each type of digital reading user portrait.and summarizes the factors that affect all types of users to pay for digital reading

. Result/conclusionFinally,this paper summarizes five types of users.A means economical users,B means edit users,Cmeans conversational users,D means silent user,and E means relaxing user.For form innovation and content optimization,this paper will provide certain reference value for the future development of various digital reading platforms.means conversational users,D means silent user,and E means relaxing user.For form innovation and content optimization,this paper will provide certain reference value for the future development of various digital reading platforms.Innovation/limitationwe dig out the influence factors of each type,and point out that the different portraits for the same user in different period.In the follow-up re⁃search,we will improve the research of digital reading user portrait by collecting a larger number of specific objective data.