User Demand Analysis of English Word Learning APP Based on Text Mining—Taking the APP Bubeidanci as an Example

With the wide application of the Internet, as one of the mobile learning methods, English word learning apps are popular among college students. The homogenization between products is becoming more and more obvious. Exploring the new needs of users is becoming the next growth point of such apps. Therefore, it is particularly necessary to study the user needs of such apps. This paper uses the combination of text mining technology and questionnaire survey to collect user comments, preprocess comment data, standardize questionnaire analysis and classify user needs. Taking the app Bubeidanci as an example, the research focuses on user needs. The research indicates that, firstly, this kind of apps can develop and improve the functions that are related to English word pronunciation, and enhance the British pronunciation and American pronunciation modes of necessary words; secondly, a simple interface can improve user satisfaction; thirdly, this kind of apps should put the innovation points on the notes and import/export wordbook; fourthly, the apps should add the function of “modifying” the process of memorizing words, such as word interpretation change and picture assisted memory; fifthly, the apps can add functions such as checking-in learning, studying in teams and student sharing; sixthly, the apps can develop English article reading, word spelling and dictation functions; lastly, the apps can innovate the profit model and continue to explore the payment functions such as vocabulary payment and membership system.