Abstract
Companies developing mobile apps face increasing requirements such as short time to market or high quality. Furthermore, users have more influence on apps, as they can easily provide feedback on the product. Consequently, feedback is a valuable source for product improvement. Ideally, this would be done in an automated way. However, because of the limitations of understanding of natural language by machines, this is not possible in a satisfactory way. We have created a quality assurance process that makes use of feedback by applying lightweight analyses in order to enable product managers to take decisions. Some aspects of our process are the inclusion of emojis to reveal emotions, the detection of trends, as well as the derivation of improvement suggestions. With examples from popular apps, we show the practical application of our process.
Keywords
- Quality assurance
- Apps
- Feedback
- Product improvement
- Emojis
This is a preview of subscription content, access via your institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Elberzhager, F., Holl, K.: Towards automated capturing and processing of user feedback for optimizing mobile apps. Procedia Comput. Sci. 110, 215–221 (2017)
Scherr, S., Elbertshager, F., Holl, K.: An automated feedback-based approach to support mobile app development. In: Proceedings - 43rd Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2017, Vienna (2017)
Hussein, D.M.E.D.M.: A survey on sentiment analysis challenges. J. King Saud Univ. Eng. Sci. (2016)
Ribeiro, F., Araújo, M., Gonçalves, M., Benevenuto, F.: SentiBench - a benchmark comparison of state-of-the-practice sentiment analysis methods. EPJ Data Sci. 5(1), 1–29 (2016)
Hogenboom, A., Bal, M., Frasincar, F., Bal, D.: Towards cross-language sentiment analysis through universal star ratings. Adv. Intell. Syst. Comput. 172, 69–79 (2013)
Scherr, S., Polst, S., Müller, L., Holl, K., Elberzhager, F.: The perception of emojis for analyzing app feedback. Int. J. Interact. Mobile Technol. [submitted]
Hogenboom, A., Bal, D., Frasincar, F., Bal, M., de Jong, F., Kaymak, U.: Exploiting emoticons in sentiment analysis. In: Proceedings of the 28th Annual ACM Symposium on Applied Computing - SAC (2013)
Tauch, C., Kanjo, E.: The roles of emojis in mobile phone notifications. In: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Adjunct - UbiComp 2016, Heidelberg (2016)
Provine, R., Spencer, R., Mandell, D.: Emotional expression online. J. Lang. Soc. Psychol. 26(3), 299–307 (2007)
Unicode: Emoji Keyboard/Display Test Data for UTR #51
Ekman, P., Friesen, W.: Constants across cultures in the face and emotion. J. Pers. Soc. Psychol. 17(2), 124–129 (1971)
Lazarus, R.: Emotion and Adaption (1991)
Plutchik, R.: A general psychoevolutionary theory of emotions. In: Theorie of Emotions, pp. 3–33 (1980)
Brand Resource Center: Reactions. https://en.facebookbrand.com/assets/reactions. Accessed 2016
IBM Watson: Natural Language Understanding. Natural language processing for advanced text analysis. https://www.ibm.com/watson/services/natural-language-understanding/
Hu, N., Pavlou, P., Zhang, J.: Can online reviews reveal a product’s true quality? In: Proceedings of the 7th ACM conference on Electronic commerce - EC 2006, Michigan (2006)
Shepherd, M.: How To Use Snapchat’s New Snap Map & Become A Social Media Master On The Go. https://www.bustle.com/p/how-to-use-snapchats-new-snap-map-become-a-social-media-master-on-the-go-65941. Accessed 21 June 2017
Snapchat Support: Snapchat Support on Twitter. https://twitter.com/snapchatsupport/status/890660305742647297?lang=en. Accessed 27 July 2017
Waton, C.: Snapchat update: more than 800,000 angry users sign petition to change redesign. https://www.theguardian.com/technology/2018/feb/13/snapchat-update-redesign-users-sign-petition-undo-new-change-back. Accessed 13 Feb 2018
Carman, A.: Instagram bug makes user accounts appear to be deleted. https://www.theverge.com/2017/7/6/15929478/instagram-deleted-accounts-why. Accessed 06 July 2018
Crook, J.: Instagram is down for some users. https://techcrunch.com/2017/07/26/instagram-is-down-for-some-users/?guccounter=1. Accessed 26 July 2017
Wagstaff, K.: Tinder crashed and now love is dead. https://mashable.com/2016/09/01/tinder-is-down/?europe=true#xXvetVZqJSqU. Accessed 02 Sept 2016
Fingas, J.: Tinder suffers sign-in problems following Facebook’s privacy changes. https://www.engadget.com/2018/04/04/tinder-sign-in-problems-following-facebook-changes/. Accessed 04 Apr 2018
Instagram Engineering: Emojineering Part 1: Machine Learning for Emoji Trends. https://engineering.instagram.com/emojineering-part-1-machine-learning-for-emoji-trendsmachine-learning-for-emoji-trends-7f5f9cb979ad. Accessed 2018
Ljubešić, N., Fišer, D.: A global analysis of emoji usage. In: Proceedings of the 10th Web as Corpus Workshop, Berlin (2016)
Acknowledgments
The research described in this paper was performed in the project Opti4Apps funded by the German Federal Ministry of Education and Research (BMBF) (grant no. 02K14A182). We thank Sonnhild Namingha for proofreading.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Scherr, S.A., Elberzhager, F., Meyer, S. (2019). Listen to Your Users – Quality Improvement of Mobile Apps Through Lightweight Feedback Analyses. In: Winkler, D., Biffl, S., Bergsmann, J. (eds) Software Quality: The Complexity and Challenges of Software Engineering and Software Quality in the Cloud. SWQD 2019. Lecture Notes in Business Information Processing, vol 338. Springer, Cham. https://doi.org/10.1007/978-3-030-05767-1_4
Download citation
DOI: https://doi.org/10.1007/978-3-030-05767-1_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-05766-4
Online ISBN: 978-3-030-05767-1
eBook Packages: Computer ScienceComputer Science (R0)