基于大数据分析的金融类APP用户需求研究
Research on User Demands of Financial APP Based on Big Data Analysis

在大数据时代，各大金融机构均在数字化转型的道路上持续发力，而面对移动互联网的挑战，数字金融已介入了金融机构各项业务的方方面面。本文运用Python算法对于金融机构APP的用户评论进行数据挖掘与分析，对收集到的30,142条文本数据展开LDA主题模型分析以找出用户的需求，并将用户需求划分为功能类、服务类和推广类。以自然语言处理中的SnowNLP算法了解用户的情感倾向，发现APP用户满意度不高，急需改善用户体验。对此，本文在量化分析的基础上提出了金融机构APP的优化建议，力图提升APP的整体运营。
In the era of big data, all major financial institutions continue to make efforts on the road of digital transformation. In the face of the challenges of the mobile Internet, digital finance has intervened in all aspects of the business of financial institutions. In this paper, we use Python algorithm to mine and analyze the user comments of financial institutions’ APPs. We analyze the collected 30,142 text data with LDA topic model to find out the users’ needs and classify them into function, service and promotion categories. Then we use SnowNLP algorithm to understand the users’ emotional tendency, finding that the APP user satisfaction is not high. As there is an urgent need to improve the user experience, based on the quantitative analysis, optimization suggestions for financial institutions’ APPs have been put forward to improve the overall operation of these APPs.