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Identifying and Classifying User Requirements in Online Feedback via Crowdsourcing

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Requirements Engineering: Foundation for Software Quality (REFSQ 2020)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 12045))

Abstract

[Context and motivation] App stores and social media channels such as Twitter enable users to share feedback regarding software. Due to its high volume, it is hard to effectively and systematically process such feedback to obtain a good understanding of users’ opinions about a software product. [Question/problem] Tools based on natural language processing and machine learning have been proposed as an inexpensive mechanism for classifying user feedback. Unfortunately, the accuracy of these tools is imperfect, which jeopardizes the reliability of the analysis results. We investigate whether assigning micro-tasks to crowd workers could be an alternative technique for identifying and classifying requirements in user feedback. [Principal ideas/results] We present a crowdsourcing method for filtering out irrelevant app store reviews and for identifying features and qualities. A validation study has shown positive results in terms of feasibility, accuracy, and cost. [Contribution] We provide evidence that crowd workers can be an inexpensive yet accurate resource for classifying user reviews. Our findings contribute to the debate on the roles of and synergies between humans and AI techniques.

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Notes

  1. 1.

    In this paper, user requirements are understood as “a need perceived by a stakeholder”, as per one sub-definition of requirement in the IREB Glossary [9].

  2. 2.

    Kyōryoku is a Japanese term for collaboration: literally, it combines strength with cooperation .

  3. 3.

    https://www.figure-eight.com/.

  4. 4.

    Note: because Phases 1 and 2 focus on filtering out irrelevant reviews, we take the useless category as our positives.

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Author information

Authors and Affiliations

  1. Department of Information and Computing Sciences, Utrecht University, Utrecht, Netherlands

    Martijn van Vliet, Eduard C. Groen, Fabiano Dalpiaz & Sjaak Brinkkemper

  2. Fraunhofer IESE, Kaiserslautern, Germany

    Eduard C. Groen

Authors
  1. Martijn van Vliet
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  2. Eduard C. Groen
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  3. Fabiano Dalpiaz
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  4. Sjaak Brinkkemper
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Corresponding author

Correspondence to Eduard C. Groen .

Editor information

Editors and Affiliations

  1. Computer Science, Middlesex College, Western University, London, ON, Canada

    Nazim Madhavji

  2. School of Computer Science, University College Dublin, Dublin, Ireland

    Liliana Pasquale

  3. Area della Ricerca CNR di Pisa, Istituto di Scienza e Tecnologie dell'Informazione “Alessandro Faedo”, Pisa, Italy

    Alessio Ferrari

  4. Area della Ricerca CNR di Pisa, Istituto di Scienza e Tecnologie dell'Informazione “Alessandro Faedo”, Pisa, Italy

    Stefania Gnesi

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van Vliet, M., Groen, E.C., Dalpiaz, F., Brinkkemper, S. (2020). Identifying and Classifying User Requirements in Online Feedback via Crowdsourcing. In: Madhavji, N., Pasquale, L., Ferrari, A., Gnesi, S. (eds) Requirements Engineering: Foundation for Software Quality. REFSQ 2020. Lecture Notes in Computer Science(), vol 12045. Springer, Cham. https://doi.org/10.1007/978-3-030-44429-7_11

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  • DOI: https://doi.org/10.1007/978-3-030-44429-7_11

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