Categorizing Quality Determinants in Mining User-Generated Contents
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The Mean
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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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2010 ◽
Vol 52
(9-12)
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pp. 1209-1221
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2017 ◽
Vol 3
(1)
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pp. 18
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2019 ◽
Vol 50
(2)
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pp. 132-138
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2013 ◽
pp. 167-172
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2011 ◽
Vol 4
(6)
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pp. 259-274
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