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research-article

Release Early, Release Often, and Watch Your Users' Emotions: Lessons From Emotional Patterns

Authors:

Daniel Martens,

Walid MaalejAuthors Info & Claims

IEEE Software, Volume 36, Issue 5

Pages 32 - 37

https://doi.org/10.1109/MS.2019.2923603

Published: 01 September 2019 Publication History

Abstract

App stores are highly competitive markets, and unexpected app changes might incite even loyal users to explore alternative apps. In this article, we present five release lessons, from emotional patterns identified using sentiment analysis tools, to assist app vendors maintain positive emotions and gain competitive advantages.

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Cited By

Wei JCourbis ALambolais TXu BBernard PDray GMaalej WFilkov VRay BZhou M(2024)Getting Inspiration for Feature Elicitation: App Store- vs. LLM-based ApproachProceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering10.1145/3691620.3695591(857-869)Online publication date: 27-Oct-2024
https://dl.acm.org/doi/10.1145/3691620.3695591
Nayebi MKuznetsov KZeller ARuhe G(2024)Recommending and release planning of user-driven functionality deletion for mobile appsRequirements Engineering10.1007/s00766-024-00430-529:4(459-480)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1007/s00766-024-00430-5
Ferrari AHuichapa TSpoletini PNovielli NFucci DGirardi D(2023)Using Voice and Biofeedback to Predict User Engagement during Product Feedback InterviewsACM Transactions on Software Engineering and Methodology10.1145/363571233:4(1-36)Online publication date: 6-Dec-2023
https://dl.acm.org/doi/10.1145/3635712
Show More Cited By

Index Terms

Release Early, Release Often, and Watch Your Users' Emotions: Lessons From Emotional Patterns
1. Social and professional topics
2. Software and its engineering

Index terms have been assigned to the content through auto-classification.

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Information & Contributors

Information

Published In

cover image IEEE Software

IEEE Software Volume 36, Issue 5

Sept.-Oct. 2019

96 pages

ISSN:0740-7459

Issue’s Table of Contents

Copyright © 2019.

Publisher

IEEE Computer Society Press

Washington, DC, United States

Publication History

Published: 01 September 2019

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Citations

Cited By

Wei JCourbis ALambolais TXu BBernard PDray GMaalej WFilkov VRay BZhou M(2024)Getting Inspiration for Feature Elicitation: App Store- vs. LLM-based ApproachProceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering10.1145/3691620.3695591(857-869)Online publication date: 27-Oct-2024
https://dl.acm.org/doi/10.1145/3691620.3695591
Nayebi MKuznetsov KZeller ARuhe G(2024)Recommending and release planning of user-driven functionality deletion for mobile appsRequirements Engineering10.1007/s00766-024-00430-529:4(459-480)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1007/s00766-024-00430-5
Ferrari AHuichapa TSpoletini PNovielli NFucci DGirardi D(2023)Using Voice and Biofeedback to Predict User Engagement during Product Feedback InterviewsACM Transactions on Software Engineering and Methodology10.1145/363571233:4(1-36)Online publication date: 6-Dec-2023
https://dl.acm.org/doi/10.1145/3635712
Das SDeb NChaki NCortesi A(2023)Driving the Technology Value Stream by Analyzing App ReviewsIEEE Transactions on Software Engineering10.1109/TSE.2023.327070849:7(3753-3770)Online publication date: 1-Jul-2023
https://dl.acm.org/doi/10.1109/TSE.2023.3270708
Berhe SMaynard MKhomh F(2023)Maintenance Cost of Software Ecosystem UpdatesProcedia Computer Science10.1016/j.procs.2023.03.077220:C(608-615)Online publication date: 10-May-2023
https://dl.acm.org/doi/10.1016/j.procs.2023.03.077
Alturayeif NAljamaan HHassine J(2023)An automated approach to aspect-based sentiment analysis of apps reviews using machine and deep learningAutomated Software Engineering10.1007/s10515-023-00397-730:2Online publication date: 9-Sep-2023
https://dl.acm.org/doi/10.1007/s10515-023-00397-7
Saidani IOuni AAhasanuzzaman MHassan SMkaouer MHassan A(2022)Tracking bad updates in mobile apps: a search-based approachEmpirical Software Engineering10.1007/s10664-022-10125-627:4Online publication date: 1-Jul-2022
https://dl.acm.org/doi/10.1007/s10664-022-10125-6
Dąbrowski JLetier EPerini ASusi A(2022)Analysing app reviews for software engineering: a systematic literature reviewEmpirical Software Engineering10.1007/s10664-021-10065-727:2Online publication date: 20-Jan-2022
https://dl.acm.org/doi/10.1007/s10664-021-10065-7
Haering MStanik CMaalej W(2021)Automatically Matching Bug Reports With Related App ReviewsProceedings of the 43rd International Conference on Software Engineering10.1109/ICSE43902.2021.00092(970-981)Online publication date: 22-May-2021
https://dl.acm.org/doi/10.1109/ICSE43902.2021.00092

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