Listen to Your Users – Quality Improvement of Mobile Apps Through Lightweight Feedback Analyses

Scherr, Simon André; Elberzhager, Frank; Meyer, Selina

doi:10.1007/978-3-030-05767-1_4

Cited by 7 publications

(7 citation statements)

References 12 publications

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“…This feature may be bene cial for future app developers to consider. Of interest is the fact that only two of the six included apps had feedback surveys, despite research which indicates feedback is a valuable resource for quality improvement of mobile apps [32].…”

Section: Discussionmentioning

confidence: 99%

Mobile Applications for COVID-19: A Scoping Review of the Initial Response in Canada

Noronha

D’Elia

Coletta

et al. 2020

Preprint

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Background: The rapid outbreak of Coronavirus diseases (COVID-19) originating in Wuhan, China, and the subsequent declaration of a state of “pandemic” on March 11, 2020 has necessitated a widespread global response to manage and control the transmission, spread and impact of COVID-19. Mobile technology has been leveraged in a number of ways to control the spread of COVID-19, including to support knowledge translation. Mobile applications are accessible, acceptable, easily adopted, and have the ability to support social distancing efforts. The following review assesses the mobile applications currently available to address COVID-19 and seeks existing studies in the literature that evaluate such applications. Methods: 3 databases (Embase, Web of Science and PubMed), 2 application stores (GooglePlay and Apple’s App Store) and google search engine were searched from inception until April 05, 2020 using key words and search strings to identify relevant apps and/or literature. Reviews of the obtained results were examined by two reviewers in double-blind nature and assessed for inclusion or exclusion. Results: 36 studies, 72 websites and 312 mobile-based applications were identified through searches. 14 applications met the inclusion criteria and were analyzed. Additional eHealth tools identified through the search strategy were considered for supplemental analysis (including online dashboards and applications not available through application stores).Conclusion: This review provides a brief assessment of the goals of applications addressing COVID-19, the types of approaches being used by these applications, and draws conclusions on the needs not being met by such application-based interventions. Innovation and collaboration between government, healthcare organizations and application developers is needed to address the identified gaps and facilitate the successful harnessing of mobile applications in the management of COVID-19.

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Section: Discussionmentioning

confidence: 99%

Mobile Applications for COVID-19: A Scoping Review of the Initial Response in Canada

Noronha

D’Elia

Coletta

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…However, the SLR also highlights that opinion spam or fake review detection is one of the largest problems in the domain. Further studies on app ratings cover topics on quality improvement through lightweight feedback analyses ( Scherr et al, 2019 ), sentiment analysis of app reviews ( Guzman and Maalej ), and consistency of star ratings and reviews of popular free hybrid Android and iOS apps ( Hu et al, 2019 ).…”

Section: Background and Related Workmentioning

confidence: 99%

“…Several papers have taken advantage of this data, especially where the volume of reviews and ratings may make manual analysis impractical. Scherr et al [35] presented a lightweight framework built on the use of emojis as representative of emotive feeling and expression of an app, building from their initial findings that large numbers of textual reviews also included emojis. Beyond general opinions, Guzman and Maalej [36] presented an approach to look at user sentiment with relation to specific features and use techniques such as Natural Language Processing (NLP) to gain this insight.…”

Section: Related Work On Mining Of App Reviewsmentioning

confidence: 99%

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

Garousi

Cutting

Felderer

2022

Journal of Systems and Software

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“…Due to the nature of mobile development, updates are issued frequently, features are added and changed; the same is the case for user feedback, which is provided continuously by the user base. Scherr et al argue in [5] that feedback should be captured and analyzed side by side with continuous software evolution. Furthermore Scherr et.…”

Section: Existing Approaches For Textual User Feedback Collection and Analysismentioning

confidence: 99%

“…Users frequently give feedback and also change their minds based on recent changes of the product [4]. Therefore, data should be continuously gathered and evaluated in order to enable reaction to fast trends and implementation of changes within short release cycles [5]. As many different sources exist nowadays where users can provide feedback (e.g., app stores, social media), another central requirement is that different sources must be taken into account.…”

Section: Introductionmentioning

confidence: 99%

Establishing Continuous App Improvement by Considering Heterogenous Data Sources

Scherr

Hupp

Elberzhager

2021

Int. J. Interact. Mob. Technol.

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<p class="0abstract"><span lang="EN-US">Mobile apps have penetrated the market and are being used everywhere. Companies developing apps face increasing challenges such as short time to market or demand for high quality. Furthermore, the success of an app also depends on how users perceive its quality. Feedback provided by users influences other potential users and provides new opportunities for identifying features. Consequently, it is a valuable source of input for app developers with respect to product improvements. One form is textual feedback. This kind of feedback is usually distributed across various data sources. Therefore, it must be captured from these sources and put into one single pool of data before it can be analyzed. The analysis must take into account the peculiarities of the short release cycles and high change rate of features for mobile apps. In this article, we present User Echo Service (UES), which was built to address heterogeneous data sources. The aim of UES is to allow product managers to be able to be always up to date with the latest feedback data. Therefore, we have created an extensible architecture aimed at supporting different data sources and present the feedback collection scheduling system. This forms the prerequisite for subsequent analyses of the collected data. We discuss our solution and provide ideas for future development.</span></p>

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Listen to Your Users – Quality Improvement of Mobile Apps Through Lightweight Feedback Analyses

Cited by 7 publications

References 12 publications

Mobile Applications for COVID-19: A Scoping Review of the Initial Response in Canada

Mobile Applications for COVID-19: A Scoping Review of the Initial Response in Canada

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

Establishing Continuous App Improvement by Considering Heterogenous Data Sources

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