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Article Dans Une Revue International Journal on Interactive Design and Manufacturing Année : 2015

Customer sentiment appraisal from user-generated product reviews: a domain independent heuristic algorithm

Dilip Raghupathi
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Bernard Yannou
Romain Farel
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Résumé

Social media give new opportunities in customer survey and market survey for design inspiration with comments posted online by users spontaneously, in an oral-near language, and almost free of biases. Opinion mining techniques are being developed, especially customer sentiment analysis. These techniques are most of the time based on a text parsing and costly learning techniques based on target or domain-dependent corpora for getting a fine understanding of users' preferences. On the contrary, in this paper, we propose an overall sentiment rating algorithm, accurate enough to deliver an overall rating on a product review , without a tedious customization to a product domain or customer polarities. The developed algorithm starts by a text parsing, uses a Dictionary of Affect Language to rate the word tree leaves and uses a series of basic heuristics to calculate backward an overall sentiment rating for the review. We validate it on the example of a commercial home theatre system, comparing our automated sentiment predictions with the one of a group of fifteen test subjects, resulting in a satisfactory correlation.
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Dates et versions

hal-01158609 , version 1 (24-02-2020)

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Dilip Raghupathi, Bernard Yannou, Romain Farel, Emilie Poirson. Customer sentiment appraisal from user-generated product reviews: a domain independent heuristic algorithm. International Journal on Interactive Design and Manufacturing, 2015, 9 (3), pp.201-211. ⟨10.1007/s12008-015-0273-4⟩. ⟨hal-01158609⟩
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