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Categorizing Quality Determinants in Mining User-Generated Contents

Author

Listed:
  • Federico Barravecchia

    (Department of Management and Production Engineering (DIGEP), Politecnico di Torino, 10129 Torino, Italy)

  • Luca Mastrogiacomo

    (Department of Management and Production Engineering (DIGEP), Politecnico di Torino, 10129 Torino, Italy)

  • Fiorenzo Franceschini

    (Department of Management and Production Engineering (DIGEP), Politecnico di Torino, 10129 Torino, Italy)

Abstract

User-Generated Contents (UGCs) are gaining increasing popularity as a source of valuable information for companies to manage the quality of their products, services and Product-Service Systems (PSS). This paper aims at proposing a novel approach to identify and categorize quality determinants through the analysis of an extensive database of UGCs. In detail, this paper applies a topic modeling algorithm (Structural Topic Model) to identify quality determinants and introduces the Mean Rating Proportion measurement for their classification into three categories: negative, positive and neutral quality determinants. The application of the proposed methodology is exemplified through the analysis of a PSS case study (car-sharing).

Suggested Citation

  • Federico Barravecchia & Luca Mastrogiacomo & Fiorenzo Franceschini, 2020. "Categorizing Quality Determinants in Mining User-Generated Contents," Sustainability, MDPI, vol. 12(23), pages 1-11, November.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:23:p:9944-:d:452451
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    References listed on IDEAS

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