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

[1]  A. Blom,et al.  Barriers to the Large-Scale Adoption of the COVID-19 Contact-Tracing App in Germany: Survey Study. , 2020, Journal of medical Internet research.

[2]  Stephen Farrell,et al.  Measurement-based evaluation of Google/Apple Exposure Notification API for proximity detection in a commuter bus , 2020, PloS one.

[3]  J. Hoepman.  A Critique of the Google Apple Exposure Notification (GAEN) Framework , 2020, ArXiv.

[4]  Abdul Razzaq,et al.  Sentiment Analysis of User Feedback on the HSE Contact Tracing App , 2020 .

[5]  S. Banducci,et al.  Citizens’ Attitudes to Contact Tracing Apps , 2020, Journal of Experimental Political Science.

[6]  Michel Walrave,et al.  Adoption of a Contact Tracing App for Containing COVID-19: A Health Belief Model Approach , 2020, JMIR Public Health and Surveillance.

[7]  T. Callender,et al.  Automated and partly automated contact tracing: a systematic review to inform the control of COVID-19 , 2020, The Lancet Digital Health.

[8]  M. Walrave,et al.  Tracing the COVID-19 Virus: A Health Belief Model Approach to the Adoption of a Contact Tracing App. , 2020, JMIR public health and surveillance.

[9]  Ingemar J. Cox,et al.  Digital technologies in the public-health response to COVID-19 , 2020, Nature Medicine.

[10]  Ross Anderson,et al.  BatNet: Data transmission between smartphones over ultrasound , 2020, ArXiv.

[11]  Georgios Kambourakis,et al.  Demystifying COVID-19 digital contact tracing: A survey on frameworks and mobile apps , 2020, Wirel. Commun. Mob. Comput..

[12]  Marco Iansiti,et al.  How to Get People to Actually Use Contact-Tracing Apps , 2020 .

[13]  Simon Trang,et al.  One app to trace them all? Examining app specifications for mass acceptance of contact-tracing apps , 2020, Eur. J. Inf. Syst..

[14]  E. Rizzo.  COVID-19 contact tracing apps: the ‘elderly paradox’ , 2020, Public Health.

[15]  D. Ranasinghe,et al.  Vetting Security and Privacy of Global COVID-19 Contact Tracing Applications , 2020, ArXiv.

[16]  Regio A. Michelin,et al.  A Survey of COVID-19 Contact Tracing Apps , 2020, IEEE Access.

[17]  Shaoxiong Wang,et al.  A New System for Surveillance and Digital Contact Tracing for COVID-19: Spatiotemporal Reporting Over Network and GPS , 2020, JMIR mHealth and uHealth.

[18]  C. J. Armitage,et al.  Public attitudes towards COVID‐19 contact tracing apps: A UK‐based focus group study , 2020, medRxiv.

[19]  Frauke Kreuter,et al.  Acceptability of App-Based Contact Tracing for COVID-19: Cross-Country Survey Study , 2020, JMIR mHealth and uHealth.

[20]  Jinfeng Li,et al.  COVID-19 Contact-tracing Apps: a Survey on the Global Deployment and Challenges , 2020, ArXiv.

[21]  V. Guttal,et al.  Risk assessment via layered mobile contact tracing for epidemiological intervention , 2020, medRxiv.

[22]  Elissa M. Redmiles.  User Concerns & Tradeoffs in Technology-Facilitated Contact Tracing , 2020, ArXiv.

[23]  Hyunghoon Cho,et al.  Contact Tracing Mobile Apps for COVID-19: Privacy Considerations and Related Trade-offs , 2020, ArXiv.

[24]  Rick Kazman,et al.  Software Engineering in Society , 2020, IEEE Softw..

[25]  Stefan Wagner,et al.  Open Science in Software Engineering , 2019, Contemporary Empirical Methods in Software Engineering.

[26]  Dong Xuan,et al.  A Study of the Privacy of COVID-19 Contact Tracing Apps , 2020, SecureComm.

[27]  Dong Xuan,et al.  On the Accuracy of Measured Proximity of Bluetooth-Based Contact Tracing Apps , 2020, SecureComm.

[28]  Helen A. Weiss,et al.  Use of a mobile application for Ebola contact tracing and monitoring in northern Sierra Leone: a proof-of-concept study , 2019, BMC Infectious Diseases.

[29]  Nishant Jha,et al.  Mining non-functional requirements from App store reviews , 2019, Empirical Software Engineering.

[30]  Maleknaz Nayebi,et al.  Data-Driven Requirements Engineering - An Update , 2019, 2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP).

[31]  Frank Elberzhager,et al.  Listen to Your Users - Quality Improvement of Mobile Apps Through Lightweight Feedback Analyses , 2019, SWQD.

[32]  Cor-Paul Bezemer,et al.  Studying the consistency of star ratings and reviews of popular free hybrid Android and iOS apps , 2018, Empirical Software Engineering.

[33]  Mohamed Ibrahim,et al.  A Little Bird Told Me: Mining Tweets for Requirements and Software Evolution , 2017, 2017 IEEE 25th International Requirements Engineering Conference (RE).

[34]  Grant Williams,et al.  Mining Twitter Feeds for Software User Requirements , 2017, 2017 IEEE 25th International Requirements Engineering Conference (RE).

[35]  Peng Liang,et al.  Automatic Classification of Non-Functional Requirements from Augmented App User Reviews , 2017, EASE.

[36]  Maleknaz Nayebi,et al.  Crowdsourced Exploration of Mobile App Features: A Case Study of the Fort McMurray Wildfire , 2017, 2017 IEEE/ACM 39th International Conference on Software Engineering: Software Engineering in Society Track (ICSE-SEIS).

[37]  Timo Johann,et al.  On the emotion of users in app reviews , 2017 .

[38]  Alain Abran,et al.  A systematic literature review: Opinion mining studies from mobile app store user reviews , 2017, J. Syst. Softw..

[39]  Nishant Jha,et al.  Mining User Requirements from Application Store Reviews Using Frame Semantics , 2017, REFSQ.

[40]  Moira C. Norrie,et al.  UI Testing Cross-Device Applications , 2016, ISS.

[41]  C. Hart,et al.  Correlation still does not imply causation. , 2016, The lancet. Psychiatry.

[42]  Philipp Koehn,et al.  Synthesis Lectures on Human Language Technologies , 2016 .

[43]  Anne Liu,et al.  Introduction of Mobile Health Tools to Support Ebola Surveillance and Contact Tracing in Guinea , 2015, Global Health: Science and Practice.

[44]  Semantic Folding Theory And its Application in Semantic Fingerprinting , 2015, ArXiv.

[45]  Walid Maalej,et al.  Bug report, feature request, or simply praise? On automatically classifying app reviews , 2015, 2015 IEEE 23rd International Requirements Engineering Conference (RE).

[46]  A. Aslam.  Research ideas: Correlation does not imply causation , 2015, BDJ.

[47]  Moira C. Norrie,et al.  XDSession: integrated development and testing of cross-device applications , 2015, EICS.

[48]  Cameron Browne,et al.  Modeling contact tracing in outbreaks with application to Ebola. , 2015, Journal of theoretical biology.

[49]  Ahmed E. Hassan,et al.  What Do Mobile App Users Complain About? , 2015, IEEE Software.

[50]  Eduard C. Groen,et al.  Towards Crowd-Based Requirements Engineering A Research Preview , 2015, REFSQ.

[51]  Oksana Zelenko,et al.  Mobile App Rating Scale: A New Tool for Assessing the Quality of Health Mobile Apps , 2015, JMIR mHealth and uHealth.

[52]  Peter J. Bentley,et al.  Investigating Country Differences in Mobile App User Behavior and Challenges for Software Engineering , 2015, IEEE Transactions on Software Engineering.

[53]  Anna Perini,et al.  An ontology of online user feedback in software engineering , 2015, Appl. Ontology.

[54]  Walid Maalej,et al.  How Do Users Like This Feature? A Fine Grained Sentiment Analysis of App Reviews , 2014, 2014 IEEE 22nd International Requirements Engineering Conference (RE).

[55]  Philippe Kruchten,et al.  Real Challenges in Mobile App Development , 2013, 2013 ACM / IEEE International Symposium on Empirical Software Engineering and Measurement.

[56]  Walid Maalej,et al.  User feedback in the appstore: An empirical study , 2013, 2013 21st IEEE International Requirements Engineering Conference (RE).

[57]  Rachel Harrison,et al.  Retrieving and analyzing mobile apps feature requests from online reviews , 2013, 2013 10th Working Conference on Mining Software Repositories (MSR).

[58]  Carles Gomez,et al.  Overview and Evaluation of Bluetooth Low Energy: An Emerging Low-Power Wireless Technology , 2012, Sensors.

[59]  Bing Liu,et al.  Sentiment Analysis and Opinion Mining , 2012, Synthesis Lectures on Human Language Technologies.

[60]  Vahid Garousi.  Evidence-Based Insights about Issue Management Processes: An Exploratory Study , 2009, ICSP.

[61]  Per Runeson,et al.  Guidelines for conducting and reporting case study research in software engineering , 2009, Empirical Software Engineering.

[62]  Jackie Fenn,et al.  Mastering the Hype Cycle: How to Choose the Right Innovation at the Right Time , 2008 .

[63]  Jennifer Keahey,et al.  Policymaking for a Good Society: The Social Fabric Matrix Approach to Policy Analysis and Program Evaluation , 2007 .

[64]  Hanna M. Wallach,et al.  Topic modeling: beyond bag-of-words , 2006, ICML.

[65]  Hans Hagen,et al.  Methods for Presenting Statistical Information: The Box Plot , 2006, VLUDS.

[66]  Claes Wohlin,et al.  Experimentation in software engineering: an introduction , 2000 .

[67]  R. Davidson.  'Searching for Mary, Glasgow': contact tracing for sexually transmitted diseases in twentieth-century Scotland. , 1996, Social history of medicine : the journal of the Society for the Social History of Medicine.

[68]  V. Basili.  Software modeling and measurement: the Goal/Question/Metric paradigm , 1992 .