Advertisement

Investigating Users’ Experiences and Attitudes Towards Mobile Apps’ Reviews

  • Omar AsiriEmail author
  • Carl K. ChangEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10902)

Abstract

One of the daily routines of the smartphone users is using the mobile applications. Individuals explore the app stores and select a potential app. The selection procedure is affected by the information that the app stores display for each app. Reviews of the apps are an important factor in making decisions to select an app. Likewise, Users experiences and attitudes are affected by the information that they read and see on the interface of apps’ reviews. In our study, we aim to investigate the users’ experiences and attitudes towards mobile apps’ reviews. To achieve our goal, we constructed a survey consists of statements divided into five categories to collect a variety of data about the users’ experience and attitude. The questionnaire’s categories were designed to generate data regarding users’ experiences and attitudes when selecting apps. Likewise, to investigate the criteria that users set to evaluate the apps’ quality. Moreover, participants were asked about their experiences with the comments section in the apps’ reviews. Also, investigating if there are complaints regarding the reviews’ comments. Furthermore, we investigated what users can know from the interface of the mobile apps reviews in the app stores. We had 102 participants in our survey. Our results showed that free apps, especially if there is a need for the app, have the most chance to be installed even with a lower rate. We also found that, besides the apps’ rating and download statistics, users tend to adapt self-judgment for determining the apps’ quality. Regarding the reviews’ comments, users wish there is a way to limit the length of the reviews. Users like the reviews that are short and specific. We found that the current interface design of the review needs revisions to help users to be aware of critical apps-related issues such as apps’ permissions.

Keywords

Apps’ reviews Users’ experiences Users’ attitudes Mobile apps Reviews’ interface 

Notes

Acknowledgment

Authors would like to thank all participants who spent their valuable time to participate in this study. In addition, we appreciate the University of Tabuk, Saudi Arabia for funding the first author.

References

  1. 1.
    App stores: number of apps in leading app stores 2017. In: Statista (2017). https://www.statista.com/statistics/276623/number-of-apps-available-in-leading-app-stores/. Accessed 5 Sept 2017
  2. 2.
    Pagano, D., Maalej, W.: User feedback in the appstore: an empirical study. In: 2013 21st IEEE International on Requirements Engineering Conference (RE), pp. 125–134. IEEE (2013)Google Scholar
  3. 3.
    Li, H., Zhang, L., Zhang, L., Shen, J.: A user satisfaction analysis approach for software evolution. In: 2010 IEEE International Conference on Progress in Informatics and Computing (PIC), pp. 1093–1097. IEEE (2010)Google Scholar
  4. 4.
    Palomba, F., Linares-Vasquez, M., Bavota, G., et al.: User reviews matter! Tracking crowdsourced reviews to support evolution of successful apps. In: 2015 IEEE International Conference on Software Maintenance and Evolution (ICSME), pp. 291–300. IEEE (2015)Google Scholar
  5. 5.
    Harman, M., Jia, Y., Zhang, Y.: App store mining and analysis: MSR for app stores. In: Proceedings of the 9th IEEE Working Conference on Mining Software Repositories, pp. 108–111. IEEE Press (2012)Google Scholar
  6. 6.
    Kim, H.-W., Lee, H.L., Son, J.E.: An exploratory study on the determinants of smartphone app purchase. In: The 11th International DSI and the 16th APDSI Joint Meeting, Taipei, Taiwan (2011)Google Scholar
  7. 7.
    Mudambi, S.M., Schuff, D.: What makes a helpful review? A study of customer reviews on Amazon.com. MIS Q. 34, 185–200 (2010)CrossRefGoogle Scholar
  8. 8.
    Finkelstein, A., Harman, M., Jia, Y., et al.: App store analysis: mining app stores for relationships between customer, business and technical characteristics. RN 14:10 (2014)Google Scholar
  9. 9.
    Iacob, C., Harrison, R., Veerappa, V.: What are you complaining about ?: A study of online reviews of mobile applications. In: Proceedings 27th International BCS Human Computer Interaction Conference, pp. 1–6 (2013)Google Scholar
  10. 10.
    Panichella, S., Di Sorbo, A., Guzman, E., et al.: How can i improve my app? Classifying user reviews for software maintenance and evolution. In: 2015 IEEE International Conference on Software Maintenance and Evolution (ICSME), pp. 281–290. IEEE (2015)Google Scholar
  11. 11.
    Platzer, E.: Opportunities of automated motive-based user review analysis in the context of mobile app acceptance. In: CECIIS-2011, pp. 309–316 (2011)Google Scholar
  12. 12.
    Hu, N., Pavlou, P., Zhang, J.: Can online reviews reveal a product’s true quality?: Empirical findings and analytical modeling of online word-of-mouth communication. In: Proceedings 7th ACM Conference Electron Commerce, pp. 324–330 (2006).  https://doi.org/10.1145/1134707.1134743
  13. 13.
    Tian, Y., Nagappan, M., Lo, D., Hassan, A.E.: What are the characteristics of high-rated apps? A case study on free android applications. In: 2015 IEEE 31st International Conference on Software Maintenance and Evolution, ICSME 2015 – Proceedings, pp. 301–310 (2015)Google Scholar
  14. 14.
    Guzman, E., Maalej, W.: How do users like this feature? A fine grained sentiment analysis of app reviews. In: 2014 IEEE 22nd International Requirements Engineering Conference (RE), pp. 153–162. IEEE (2014)Google Scholar
  15. 15.
    Kuehnhausen, M., Frost, V.S.: Trusting smartphone apps? To install or not to install, that is the question. In: 2013 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support, CogSIMA 2013, pp. 30–37 (2013)Google Scholar
  16. 16.
    Chin, E., Felt, A.P., Sekar, V., Wagner, D.: Measuring user confidence in smartphone security and privacy. In: Proceedings of the Eighth Symposium on Usable Privacy and Security - SOUPS 2012, p. 1 (2012)Google Scholar
  17. 17.
    Matthews, T., Pierce, J., Tang, J.: No smart phone is an island: the impact of places, situations, and other devices on smart phone use. IBM RJ10452, pp. 1–10 (2009)Google Scholar
  18. 18.
    Hoon, L., Vasa, R., Schneider, J.-G., Mouzakis, K.: A preliminary analysis of vocabulary in mobile app user reviews. In: Proceedings of the 24th Australian Computer-Human Interaction Conference, pp. 245–248. ACM (2012)Google Scholar
  19. 19.
    Tian, Y., Liu, B., Dai, W., et al.: Study on user’ s attitude and behavior towards android application update notification. Usenix, Menlo Park, CA (2014)Google Scholar
  20. 20.
    Nayebi, M., Adams, B., Ruhe, G.: Release practices for mobile apps – what do users and developers think? In: 2016 IEEE 23rd International Conference on Software Analysis, Evolution, and Reengineering SANER, pp. 552–562 (2016)Google Scholar
  21. 21.
    McIlroy, S., Ali, N., Hassan, A.E.: Fresh apps: an empirical study of frequently-updated mobile apps in the Google play store. Empir. Softw. Eng. 21, 1346–1370 (2016)CrossRefGoogle Scholar
  22. 22.
    Kelley, P.G., Consolvo, S., Cranor, L.F., Jung, J., Sadeh, N., Wetherall, D.: A conundrum of permissions: installing applications on an android smartphone. In: Blyth, J., Dietrich, S., Camp, L.J. (eds.) FC 2012. LNCS, vol. 7398, pp. 68–79. Springer, Heidelberg (2012).  https://doi.org/10.1007/978-3-642-34638-5_6CrossRefGoogle Scholar
  23. 23.
    Rajivan, P., Camp, J.: Influence of privacy attitude and privacy cue framing on android app choices. In: Twelfth Symposium Usable Privacy and Security, pp. 1–7 (2016)Google Scholar
  24. 24.
    Shklovski, I., Mainwaring, S.D., Skúladóttir, H.H., Borgthorsson, H.: Leakiness and creepiness in app space. In: Proceedings of the 32nd Annual ACM Conference on Human Factors in Computing Systems - CHI 2014, pp. 2347–2356 (2014)Google Scholar
  25. 25.
    Felt, A.P., Ha, E., Egelman, S., et al.: Android permissions: user attention, comprehension, and behavior. In: Proceedings of the Eighth Symposium on Usable Privacy and Security, SOUPS 2012, pp. 1–14. ACM, Washington, D.C. (2012)Google Scholar
  26. 26.
    Felt, A.P., Egelman. S., Wagner, D.: I’ve got 99 problems, but vibration ain’t one: a survey of smartphone users’ concerns. In: Proceedings of the Second ACM Workshop on Security and Privacy in Smartphones and Mobile Devices, pp. 33–44. ACM (2012)Google Scholar
  27. 27.
    Lin, J., Amini, S., Hong, J.I., et al.: Expectation and purpose: understanding users’ mental models of mobile app privacy through crowdsourcing. In: Proceedings of the 2012 ACM Conference on Ubiquitous Computing, pp. 501–510. ACM (2012)Google Scholar
  28. 28.
    Stevens, R., Ganz, J., Filkov, V., et al.: Asking for (and about) permissions used by android apps. In: Proceedings of the 10th Working Conference on Mining Software Repositories, pp. 31–40. IEEE Press (2013)Google Scholar
  29. 29.
    Nagappan, M., Shihab, E.: Future Trends in Software Engineering Research for Mobile Apps. In: 2016 IEEE 23rd International Conference on Software Analysis, Evolution, and Reengineering (SANER), pp. 21–32 (2016)Google Scholar
  30. 30.
    Li, D., Hao, S., Gui, J., Halfond, W.G.: An empirical study of the energy consumption of android applications. In: 2014 IEEE International Conference on Software Maintenance and Evolution (ICSME), pp. 121–130. IEEE (2014)Google Scholar
  31. 31.
    Khalid, H.: On identifying user complaints of iOS apps. In: International Conference on Software Engineering, pp. 1474–1476. IEEE Press, Piscataway (2013)Google Scholar
  32. 32.
    Khalid, H., Shihab, E., Nagappan, M., Hassan, A.E.: What do mobile app users complain about? IEEE Softw. 32, 70–77 (2015).  https://doi.org/10.1109/MS.2014.50CrossRefGoogle Scholar
  33. 33.
    Hedegaard, S., Simonsen, J.G.: Extracting usability and user experience information from online user reviews. In: SIGCHI Conference on Human Factors in Computing Systems - CHI 2013, p. 2089 (2013)Google Scholar
  34. 34.
    Liu, B., Lin, J., Sadeh, N.: Reconciling mobile app privacy and usability on smartphones: could user privacy profiles help? In: Proceedings 23rd International Conference World Wide Web, pp. 201–212 (2014).  https://doi.org/10.1145/2566486.2568035
  35. 35.
    Privitera, G.J.: Student Study Guide With IBM® SPSS® Workbook for Essential Statistics for the Behavioral Sciences. SAGE Publications, Thousand Oaks (2015)Google Scholar
  36. 36.
    Müller, H., Sedley, A., Ferrall-Nunge, E.: Survey research in HCI. In: Olson, J., Kellogg, W. (eds.) Ways of Knowing in HCI, pp. 229–266. Springer, New York (2014)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Iowa State UniversityAmesUSA

Personalised recommendations