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Mining user reviews of COVID contact-tracing apps: An exploratory analysis of nine European apps
Queen's University Belfast, GBR.
Queen's University Belfast, GBR.
Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för programvaruteknik.ORCID-id: 0000-0003-3818-4442
2022 (engelsk)Inngår i: Journal of Systems and Software, ISSN 0164-1212, E-ISSN 1873-1228, Vol. 184, artikkel-id 111136Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Context: More than 78 countries have developed COVID contact-tracing apps to limit the spread of coronavirus. However, many experts and scientists cast doubt on the effectiveness of those apps. For each app, a large number of reviews have been entered by end-users in app stores. Objective: Our goal is to gain insights into the user reviews of those apps, and to find out the main problems that users have reported. Our focus is to assess the “software in society” aspects of the apps, based on user reviews. Method: We selected nine European national apps for our analysis and used a commercial app-review analytics tool to extract and mine the user reviews. For all the apps combined, our dataset includes 39,425 user reviews. Results: Results show that users are generally dissatisfied with the nine apps under study, except the Scottish (“Protect Scotland”) app. Some of the major issues that users have complained about are high battery drainage and doubts on whether apps are really working. Conclusion: Our results show that more work is needed by the stakeholders behind the apps (e.g., app developers, decision-makers, public health experts) to improve the public adoption, software quality and public perception of these apps. © 2021 Elsevier Inc.

sted, utgiver, år, opplag, sider
Elsevier Inc. , 2022. Vol. 184, artikkel-id 111136
Emneord [en]
Contact-tracing, COVID, Data mining, Mobile apps, Software engineering, Software in society, User reviews, Application programs, Computer software selection and evaluation, Decision making, App stores, Contact tracing, Coronaviruses, End-users, Exploratory analysis, Gain insight, Mobile app
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Identifikatorer
URN: urn:nbn:se:bth-22400DOI: 10.1016/j.jss.2021.111136ISI: 000722219800001Scopus ID: 2-s2.0-85118981042OAI: oai:DiVA.org:bth-22400DiVA, id: diva2:1614677
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Tilgjengelig fra: 2021-11-26 Laget: 2021-11-26 Sist oppdatert: 2021-12-03bibliografisk kontrollert

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