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Towards Automated Taxonomy Generation for Grouping App Reviews: A Preliminary Empirical Study

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Quality of Information and Communications Technology (QUATIC 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1266))

Abstract

App reviews often reflect end-users’ requests, issues or suggestions for supporting app maintenance and evolution. Hence, researchers have evaluated several classification approaches for identifying and classifying such app reviews. However, these classification approaches are driven by manually derived taxonomies. This is a limitation given the burden of human involvement, numerous app reviews and dependency on the availability of domain knowledge to perform classification. In this pilot study, we develop and evaluate a novel approach towards the automatic generation of a dynamic taxonomy that groups related app reviews. Our approach uses natural language processing, feature engineering and word sense disambiguation to automatically generate the taxonomy. We validated the proposed approach with app reviews extracted from the popular My Tracks app, where outcomes revealed a 72% match with a manual taxonomy generated from domain knowledge provided by humans. Our approach shows promise for rapidly supporting software maintenance and evolution.

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Notes

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    https://tinyurl.com/y4ny72jy.

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Authors and Affiliations

  1. Department of Information Science, University of Otago, Dunedin, New Zealand

    Saurabh Malgaonkar, Sherlock A. Licorish & Bastin Tony Roy Savarimuthu

Authors
  1. Saurabh Malgaonkar
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  2. Sherlock A. Licorish
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  3. Bastin Tony Roy Savarimuthu
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Corresponding author

Correspondence to Saurabh Malgaonkar .

Editor information

Editors and Affiliations

  1. Brunel University, London, UK

    Martin Shepperd

  2. Lisbon University Institute, Lisbon, Portugal

    Fernando Brito e Abreu

  3. University of Lisbon, Lisbon, Portugal

    Alberto Rodrigues da Silva

  4. University of Castilla-La Mancha, Talavera de la Reina, Spain

    Ricardo Pérez-Castillo

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Malgaonkar, S., Licorish, S.A., Savarimuthu, B.T.R. (2020). Towards Automated Taxonomy Generation for Grouping App Reviews: A Preliminary Empirical Study. In: Shepperd, M., Brito e Abreu, F., Rodrigues da Silva, A., Pérez-Castillo, R. (eds) Quality of Information and Communications Technology. QUATIC 2020. Communications in Computer and Information Science, vol 1266. Springer, Cham. https://doi.org/10.1007/978-3-030-58793-2_10

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  • DOI: https://doi.org/10.1007/978-3-030-58793-2_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58792-5

  • Online ISBN: 978-3-030-58793-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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