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- W4324152521 abstract "Abstract The Threshold-based Naïve Bayes (Tb-NB) classifier is introduced as a (simple) improved version of the original Naïve Bayes classifier. Tb-NB extracts the sentiment from a Natural Language text corpus and allows the user not only to predict how much a sentence is positive (negative) but also to quantify a sentiment with a numeric value. It is based on the estimation of a single threshold value that concurs to define a decision rule that classifies a text into a positive (negative) opinion based on its content. One of the main advantage deriving from Tb-NB is the possibility to utilize its results as the input of post-hoc analysis aimed at observing how the quality associated to the different dimensions of a product or a service or, in a mirrored fashion, the different dimensions of customer satisfaction evolve in time or change with respect to different locations. The effectiveness of Tb-NB is evaluated analyzing data concerning the tourism industry and, specifically, hotel guests’ reviews from all hotels located in the Sardinian region and available on Booking.com. Moreover, Tb-NB is compared with other popular classifiers used in sentiment analysis in terms of model accuracy, resistance to noise and computational efficiency." @default.
- W4324152521 created "2023-03-15" @default.
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- W4324152521 date "2023-03-14" @default.
- W4324152521 modified "2023-10-05" @default.
- W4324152521 title "Threshold-based Naïve Bayes classifier" @default.
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- W4324152521 doi "https://doi.org/10.1007/s11634-023-00536-8" @default.
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