OVO电子钱包基于LDA主题建模的用户评论分析

Albertus Dwiyoga Widiantoro, S.Kom., M.Kom., Bernardinus Harnadi
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引用次数: 0

摘要

印尼的金融科技OVO是无现金支付服务的重要组成部分。用户利用Playstore上的评论服务向OVO经理传达消息。每天都会有数百条评论出现,如果没有回应,这将是一个问题。潜在狄利克雷分配(LDA)模型的主题方法将用于分析用户主题的发生。基于6主题LDA模型,我们发现趋势主题在主题1中,主题概率值为0.235。主题1提到了OVO使用率高的高级服务的交易困难,而交易的易用性的总概率最低。本主题的结果可作为OVO服务提供商将其性能集中于改进OVO应用程序的参考。这项研究对服务提供商的影响是找出OVO应用程序用户讨论的主题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of User Comments Based on Topic Modeling using LDA on OVO E-Wallet
Fintech OVO in Indonesia is an important part of cashless payment services. Users take advantage of the commenting service on the Playstore to convey messages to OVO managers. Hundreds of comments always appear every day, and this if not responded to will be a problem. The topic method of the Latent Dirichlet Allocation (LDA) model will be used to analyze the occurrence of user topics. Based on the 6-topic LDA model, we found that the trending topic was in topic 1, with a topic probability value of 0.235. Topic 1 mentions transaction difficulties with premium services with high OVO usage While the ease of transactions has the lowest total probability. The results of this topic can be used as a reference for OVO service providers to focus their performance on improving OVO applications. The impact of this research on service providers is to find out the topics discussed by OVO application users.
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