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App Reviews: Breaking the User and Developer Language Barrier

  • Leonard Hoon
  • Miguel Angel Rodriguez-García
  • Rajesh Vasa
  • Rafael Valencia-GarcíaEmail author
  • Jean-Guy Schneider
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 405)

Abstract

Apple, Google and third party developers offer apps across over twenty categories for various smart mobile devices. Offered exclusively through the App Store and Google Play, each app allows users to review the app and their experience with it. Current literature offers a general statistical picture of these reviews, and a broad overview of the nature of discontent of apps. However, we do not yet have a good framework to classify user reviews against known software quality attributes like performance or usability. In order to close this gap, in this paper, we develop an ontology encompassing software attributes derived from software quality models. This decomposes into approximately five thousand words that users employ to review apps. By identifying a consistent set of vocabulary that users communicate with, we can sanitise large datasets to extract stakeholder actionable information from reviews. The findings offered in this paper assists future app review analysis by bridging end-user communication and software engineering vocabulary.

Keywords

Ontology development Semantic annotation Sentiment analysis User reviews 

Notes

Acknowledgments

This work has been supported by the Spanish private foundation Fundación Cultural Privada Esteban Romero through its research stays grants.

References

  1. 1.
    Hoon, L., Vasa, R., Martino, G.Y., Schneider, J.G., Mouzakis, K.: Awesome! conveying satisfaction on the app store. In: 25th Australian Computer-Human Interaction Conference (2013)Google Scholar
  2. 2.
    Harman, M., Jia, Y., & Zhang, Y.: App store mining and analysis: MSR for app stores. In: 9th IEEE Working Conference on Mining Software Repositories, pp. 108–111. IEEE Press (2012)Google Scholar
  3. 3.
    Vasa, R., Hoon, L., Mouzakis, K., Noguchi, A.: A preliminary analysis of mobile app user reviews. In: 24th Australian Computer-Human Interaction Conference, pp. 241–244 (2012)Google Scholar
  4. 4.
    Hoon, L., Vasa, R., Schneider, J.G., Grundy, J.: An Analysis of the Mobile App Review Landscape: Trends and Implications. Faculty of Information and Communication Technologies, Swinburne University of Technology, Melbourne, Australia, Tech. Rep. http://hdl.handle.net/1959.3/352848
  5. 5.
    Iacob, C., Harrison R.: Retrieving and analyzing mobile apps feature requests from online reviews. In: 2013 10th IEEE Working Conference on Mining Software Repositories (MSR), pp. 41–44. IEEE (2013)Google Scholar
  6. 6.
    Platzer, E.: Opportunities of automated motive-based user review analysis in the context of mobile app acceptance. In: 22nd Central European Conference on Information and Intelligent Systems. CECIIS ’11, pp. 309–316 (2011)Google Scholar
  7. 7.
    Hoon, L., Vasa, R., Schneider, J.G., Mouzakis, K.: A Preliminary Analysis of Vocabulary in Mobile App User Reviews. In: 24th Australian Computer-Human Interaction Conference, pp. 245–248 (2012)Google Scholar
  8. 8.
    Binkley, D., Hearn, M., Lawrie, D.: Improving identifier informativeness using part of speech information. In: 8th Working Conference on Mining Software Repositories, MSR ’11, pp. 203–206. ACM, New York (2011)Google Scholar
  9. 9.
    De Nicola, A., Missikoff, M., Navigli, R.: A software engineering approach to ontology building. Inf. Syst. 34(2), 258–275 (2009)CrossRefGoogle Scholar
  10. 10.
    Li, Y.F., Zhang, H.: Integrating software engineering data using semantic web technologies. In: 8th Working Conference on Mining Software Repositories. MSR ’11, pp. 211–214. ACM, New York (2011)Google Scholar
  11. 11.
    McCall, J.A., Richards, P. K., Walters, G.F.: Factors in Software Quality. General Electric, National Technical Information Service (1977)Google Scholar
  12. 12.
    Boehm, B.W., Brown, J.R., Kaspar, H., Lipow, M., MacLeod, G.J., Merrit, M.J.: Characteristics of software quality. North-Holland Publishing Company, vol. 1 (1978)Google Scholar
  13. 13.
    ISO/IEC 9126-4 Software Engineering—Product Quality—Part 4: Quality In Use Metrics, ISO/IEC, Tech. Rep (2002)Google Scholar
  14. 14.
    Studer, R., Benjamins, V.R., Fensel, D.: Knowledge engineering: principles and methods. Data Knowl. Eng. 25(1), 161–197 (1998)CrossRefzbMATHGoogle Scholar
  15. 15.
    Ruiz-Martínez, J.M., Valencia-García, R., Martínez-Béjar, R., Hoffmann, A.: BioOntoVerb: a top level ontology based framework to populate biomedical ontologies from texts. Knowl. Based Syst. 36, 68–80 (2012)CrossRefGoogle Scholar
  16. 16.
    Prieto-González, L., Stantchev, V., Colomo-Palacios, R.: Applications of ontologies in knowledge representation of human perception. Int. J. Metadata Semant. Ontol. 9(1), 74–80 (2014)CrossRefGoogle Scholar
  17. 17.
    Colomo-Palacios, R., Garcia-Crespo, A., Soto-Acosta, P., Ruano-Mayoral, M., Jiménez-López, D.: A case analysis of semantic technologies for R&D intermediation information management’. Int. J. Inf. Manage. 30(5), 465–469 (2010)CrossRefGoogle Scholar
  18. 18.
    Lupiani-Ruiz, E., García-Manotas, I., Valencia-García, R., García-Sánchez, F., Castellanos-Nieves, D., Fernández-Breis, J.T., Camón-Herrero, J.B.: Financial news semantic search engine. Expert Syst. Appl. 38(12), 15565–15572 (2011)CrossRefGoogle Scholar
  19. 19.
    Hernández-González, Y., García-Moreno, C., Rodríguez-García, M.Á., Valencia-García, R., García-Sánchez, F.: A semantic-based platform for R&D project funding management. Comput. Ind. 65(5), 850–861 (2014)CrossRefGoogle Scholar
  20. 20.
    Rodríguez-García, M.Á., Valencia-García, R., García-Sánchez, F., Samper-Zapater, J.J.: Ontology-based annotation and retrieval of services in the cloud. Knowl. Based Syst. 56, 15–25 (2014)CrossRefGoogle Scholar
  21. 21.
    Oren, E., Moller, K., Scerri, S., Handschuh, S., Sintek, M.: What are semantic annotations. Relatório técnico, DERI, Galway (2006)Google Scholar
  22. 22.
    Reeve, L., Han, H.: Survey of semantic annotation platforms. In: 2005 ACM symposium on Applied computing, pp. 1634–1638. ACM (2005)Google Scholar
  23. 23.
    Kiyavitskaya, N., Zeni, N., Cordy, J.R. Mich, L., Mylopoulos, J.: Semi-automatic semantic annotations for web documents. In: SWAP (2005)Google Scholar
  24. 24.
    Cunningham, H. Tablan, V. Roberts, A., Bontcheva, K.: Getting more out of biomedical documents with gate’s full lifecycle open source text analytics. PLoS computational biology, vol. 9, no. 2 (2013)Google Scholar
  25. 25.
    Mouzakis, K.: Hoon, L., Rajesh, V.: Socrates Mobile App Review Dataset (2013)Google Scholar
  26. 26.
    Hu, M., & Liu, B. Mining and summarizing customer reviews. In: 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. pp. 168–177. ACM (2004)Google Scholar
  27. 27.
    Fellbaum, C.: WordNet. Wiley Online Library (1999)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Leonard Hoon
    • 1
  • Miguel Angel Rodriguez-García
    • 2
  • Rajesh Vasa
    • 1
  • Rafael Valencia-García
    • 3
    Email author
  • Jean-Guy Schneider
    • 1
  1. 1.Faculty of Science, Engineering and TechnologySwinburne University of TechnologyMelbourneAustralia
  2. 2.Computational Bioscience Research CenterKing Abdullah University of Science and TechnologyThuwalKingdom of Saudi Arabia
  3. 3.Department of Informatics and Systems Universidad de MurciaMurciaSpain

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