User Sentiment Prediction and Analysis for Payment App Reviews Using Supervised and Unsupervised Machine Learning Approaches

Author:

Hossain Md Shamim1ORCID,Dahiya Omdev2,Al Noman Md Abdullah1ORCID

Affiliation:

1. Hajee Mohammad Danesh Science and Technology University, Bangladesh

2. Lovely Professional University, India

Abstract

Businesses must be aware of customer sentiment in order to provide the best customer service. Instead of using cash or a credit card, a user can use a payment app on a mobile device to pay for a variety of services and digital or physical goods, which is becoming increasingly popular around the world. The goal of this study is to evaluate and predict user sentiment for payment apps using supervised and unsupervised machine learning (ML) approaches. For the study's data, Google Play Store reviews of the PayPal and Google Pay apps were gathered. Following cleaning, the filtered summary sentences were assessed for positive, neutral, or negative feelings using two unsupervised and five supervised machine learning approaches. According to the findings of the current study, the majority of customer reviews for payment apps were positive, with the average number of words with negative sentiment being higher. Furthermore, recent research found that, while all ML approaches can correctly classify review text into sentiment classes, logistic regression outperforms them in terms of accuracy.

Publisher

IGI Global

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3