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Diabetes Self-management Mobile Apps Improvement Based on Users’ Reviews Classification

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Intelligent Systems Design and Applications (ISDA 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1351))

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Abstract

The feedback of mobile apps’ users by posting review comments or giving star ratings must be considered in mobile apps maintenance and evolution. In this paper, we analyze users’ reviews suggested on 10 diabetes self-management mobile apps. This analysis has been performed using text analysis, text classification and opinion analysis based on machine learning classifiers. This analysis will provide relevant information for the diabetes apps improvement.

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Author information

Authors and Affiliations

  1. Mir@cl Laboratory, University of Sfax, ISIMS, 242. 3021, Sfax, Tunisia

    Najwa Benalaya, Mariem Haoues & Asma Sellami

Authors
  1. Najwa Benalaya
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  2. Mariem Haoues
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  3. Asma Sellami
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Editor information

Editors and Affiliations

  1. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Ajith Abraham

  2. Department of Computer Science, Università degli Studi di Milano, Milan, Milano, Italy

    Vincenzo Piuri

  3. Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Niketa Gandhi

  4. Campus Centre de Créteil, Université Paris-Est Créteil, Créteil, France

    Patrick Siarry

  5. Department of Construction Management and Real Estate, Vilnius Gediminas Technical University, Vilnius, Lithuania

    Arturas Kaklauskas

  6. School of Engineering, Instituto Superior de Engenharia do Porto, Porto, Portugal

    Ana Madureira

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Benalaya, N., Haoues, M., Sellami, A. (2021). Diabetes Self-management Mobile Apps Improvement Based on Users’ Reviews Classification. In: Abraham, A., Piuri, V., Gandhi, N., Siarry, P., Kaklauskas, A., Madureira, A. (eds) Intelligent Systems Design and Applications. ISDA 2020. Advances in Intelligent Systems and Computing, vol 1351. Springer, Cham. https://doi.org/10.1007/978-3-030-71187-0_113

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