M. Alhur, Shaher Alshamari, J. Oláh, Hanadi Aldreabi
{"title":"Unsupervised Machine Learning to Identify Positive and Negative Themes in Jordanian mHealth Apps","authors":"M. Alhur, Shaher Alshamari, J. Oláh, Hanadi Aldreabi","doi":"10.4018/ijesma.313950","DOIUrl":null,"url":null,"abstract":"User opinions are crucial in the development of mobile health (mHealth) applications (apps). This study aimed to investigate and qualitatively assess consumer attitudes toward mHealth apps and the main aspects of their design. The methodology was divided into four steps: (1) data collection, (2) preprocessing, (3) sentiment analysis by valence-aware dictionary and sentiment reasoner (VADER), and (4) thematic analysis by the latent Dirichlet allocation (LDA) algorithm. These steps were implemented in 836 reviews of eight mHealth apps on app stores in Jordan. The current study offers healthcare stakeholders insight into the positive and negative aspects of mHealth apps by identifying user-preferred features and recommending improvements. The findings indicate several aspects of design that mHealth app developers may use to improve overall efficacy, including user experience, client services, usability, and adherence.","PeriodicalId":37399,"journal":{"name":"International Journal of E-Services and Mobile Applications","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of E-Services and Mobile Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijesma.313950","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Business, Management and Accounting","Score":null,"Total":0}
引用次数: 0
Abstract
User opinions are crucial in the development of mobile health (mHealth) applications (apps). This study aimed to investigate and qualitatively assess consumer attitudes toward mHealth apps and the main aspects of their design. The methodology was divided into four steps: (1) data collection, (2) preprocessing, (3) sentiment analysis by valence-aware dictionary and sentiment reasoner (VADER), and (4) thematic analysis by the latent Dirichlet allocation (LDA) algorithm. These steps were implemented in 836 reviews of eight mHealth apps on app stores in Jordan. The current study offers healthcare stakeholders insight into the positive and negative aspects of mHealth apps by identifying user-preferred features and recommending improvements. The findings indicate several aspects of design that mHealth app developers may use to improve overall efficacy, including user experience, client services, usability, and adherence.
期刊介绍：
The International Journal of E-Services and Mobile Applications (IJESMA) promotes and publishes state-of-the art research regarding different issues in the production management, delivery and consumption of e-services, self services, and mobile communication including business-to-business, business-to-consumer, government-to-business, government-to-consumer, and consumer-to-consumer e-services relevant to the interest of professionals, academic educators, researchers, and industry consultants in the field.
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