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).

Categorizing Quality Determinants in Mining User-Generated Contents / Barravecchia, Federico; Mastrogiacomo, Luca; Franceschini, Fiorenzo. - In: SUSTAINABILITY. - ISSN 2071-1050. - STAMPA. - 12:23, Ref.9944(2020), pp. 1-12. [10.3390/su12239944]

Categorizing Quality Determinants in Mining User-Generated Contents

Federico Barravecchia;Luca Mastrogiacomo;Fiorenzo Franceschini
2020

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).
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11583/2856917