基于Google Playstore评论的Zoom Cloud会议应用的卷积神经网络情感分析

Rina Refianti, Novia Anggraeni
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引用次数: 0

摘要

Zoom Cloud Meetings是一个用于进行视频会议的应用程序。在Google Play商店,Zoom Cloud Meeting应用程序获得了3.8分的评分,截至2021年3月,下载量增加了5亿次。该应用程序有很多优点,比如不受对话暂停的干扰,视频和音频质量都很好。这些应用程序所拥有的优势需要开发,以便应用程序服务变得更好。出于这个原因,需要用户评论来查看用户对应用程序的满意度,以便他们可以确定将来可以开发的服务。基于此,本研究创建了一个基于web的应用程序,该应用程序可以使用卷积神经网络(CNN)方法对Zoom Cloud Meetings应用程序的用户评论进行分类并计算准确率值。这个应用程序是使用Flask框架和Python编程语言构建的。模型训练使用TensorFlow库进行。然后使用两个阶段的测试对已制作的应用程序进行测试,即带有黑盒的系统测试和数据测试。通过系统测试,发现网站运行良好,并利用测试数据进行数据测试,准确率达到91.5%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sentiment Analysis Using Convolutional Neural Network Method to Classify Reviews on Zoom Cloud Meetings Application Based on Reviews on Google Playstore
Zoom Cloud Meetings is an application that is used to conduct video conferencing. On the Google Play Store, the Zoom Cloud Meeting application received a rating of 3.8, with 500 million more downloads as of March 2021. The application has many advantages, such as not being disturbed by pauses in conversation and having good video and audio quality. The advantages possessed by these applications require development so that application services are getting better. For this reason, user reviews are needed to see user satisfaction with the application so that they can determine services that can be developed in the future. Based on this, this research was created to create a web-based application that can classify user reviews of the Zoom Cloud Meetings application using the Convolutional Neural Network (CNN) method and calculate the accuracy value. This application is built using the Flask framework and the Python programming language. Model training is carried out using the TensorFlow library. Applications that have been made are then tested using two stages of testing, namely system testing with black box and data testing. Based on system testing, it was found that the website can run well, and for data testing using test data, the accuracy result is 91.5%.
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