2016
DOI: 10.1155/2016/5968705
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Combining Review Text Content and Reviewer-Item Rating Matrix to Predict Review Rating

Abstract: E-commerce develops rapidly. Learning and taking good advantage of the myriad reviews from online customers has become crucial to the success in this game, which calls for increasingly more accuracy in sentiment classification of these reviews. Therefore the finer-grained review rating prediction is preferred over the rough binary sentiment classification. There are mainly two types of method in current review rating prediction. One includes methods based on review text content which focus almost exclusively o… Show more

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Cited by 6 publications
(6 citation statements)
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“…Text mining and text analytics rely on natural language-processing, pattern-discovery, and advanced presentation-layer elements such as visualization tools to extract meaningful information (Feldman and Sanger 2007), such as frequent terms, topics, sentiment polarity, or relationships, from the text. The literature on the application of opinion mining and sentiment analysis to online reviews of products and services is extensive (Gupta et al 2010;Wang et al 2016). However, in the tourism and hospitality industries, a literature survey carried out by Schuckert et al (2015b) revealed that only 8 (16%) of 50 articles published from 2003 to 2014 employed sentiment analysis.…”
Section: Text Analytics Of Online Reviewsmentioning
confidence: 99%
“…Text mining and text analytics rely on natural language-processing, pattern-discovery, and advanced presentation-layer elements such as visualization tools to extract meaningful information (Feldman and Sanger 2007), such as frequent terms, topics, sentiment polarity, or relationships, from the text. The literature on the application of opinion mining and sentiment analysis to online reviews of products and services is extensive (Gupta et al 2010;Wang et al 2016). However, in the tourism and hospitality industries, a literature survey carried out by Schuckert et al (2015b) revealed that only 8 (16%) of 50 articles published from 2003 to 2014 employed sentiment analysis.…”
Section: Text Analytics Of Online Reviewsmentioning
confidence: 99%
“…The existing literature on the employment of sentiment analysis in the online reviews of products and services is vast (Wang et al, 2016). However, the specific focus of the present study is on the works that have examined the specificities of hotel reviews.…”
Section: Related Workmentioning
confidence: 99%
“…In the existing literature, a significant amount of work on review rating prediction and text review analysis uses text and sentiment analysis [17], [18]. Further work on our proposed statistical modeling approach can be done by incorporating results from text analysis into the CUB model, such as the sentiment of the text review, thus making full use of the text review and review ratings in analyzing online review data.…”
Section: Discussionmentioning
confidence: 99%