Mining user reviews of COVID contact-tracing apps: An exploratory analysis of nine European apps

TL;DR

This study analyzes 39,425 user reviews of nine European COVID contact-tracing apps, revealing widespread dissatisfaction related to battery drain and effectiveness doubts, highlighting the need for improvements to enhance public trust and adoption.

Contribution

It provides an exploratory analysis of user feedback on COVID contact-tracing apps, identifying key issues affecting user satisfaction and app effectiveness.

Findings

Users are generally dissatisfied with most apps.

Battery drainage is a major concern.

Doubts about app effectiveness are prevalent.

Abstract

Context: More than 50 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.