2019
DOI: 10.3390/su11030913
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Sales Prediction by Integrating the Heat and Sentiments of Product Dimensions

Abstract: Online word-of-mouth (eWOM) disseminated on social media contains a considerable amount of important information that can predict sales. However, the accuracy of sales prediction models using big data on eWOM is still unsatisfactory. We argue that eWOM contains the heat and sentiments of product dimensions, which can improve the accuracy of prediction models based on multiattribute attitude theory. In this paper, we propose a dynamic topic analysis (DTA) framework to extract the heat and sentiments of product … Show more

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Cited by 6 publications
(1 citation statement)
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“…In order to anticipate daily sales, they therefore suggested an autoregressive heat-sentiment (ARHS) model that incorporates the heat and sentiments of dimensions into the benchmark prediction model. Scholars undertake an empirical analysis of the film business and find that the ARHS model predicts box office receipts for movies more accurately than other models [4].…”
Section: Introductionmentioning
confidence: 99%
“…In order to anticipate daily sales, they therefore suggested an autoregressive heat-sentiment (ARHS) model that incorporates the heat and sentiments of dimensions into the benchmark prediction model. Scholars undertake an empirical analysis of the film business and find that the ARHS model predicts box office receipts for movies more accurately than other models [4].…”
Section: Introductionmentioning
confidence: 99%