The role of entropy of review text sentiments on online WOM and movie box office sales

Lee, Jong Hyup; Jung, Sun Ho; Park, JaeHong

doi:10.1016/j.elerap.2017.03.001

Cited by 58 publications

(43 citation statements)

References 51 publications

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“…For avoiding potential multicollinearity among variables, all variables were mean centred before the interaction terms are created [61]. The estimated results are shown in Table IV.…”

Section: B Main Resultsmentioning

confidence: 99%

The Combination Signaling Effect of Text and Image on Mobile Phone Review Helpfulness - The Moderating Effect of Signaling Environment

Fan

Zhang

2020

IEEE Access

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Consumers are increasingly using both texts and images to express their opinions about products rather than using texts alone. These two types of information complement each other in influencing potential consumers' evaluation on review helpfulness. However, extant studies mainly investigate the impact of texts and images on review helpfulness independently. Based on signaling theory and level of processing theory, this study attempts to investigate the potential interaction effect of textual signal (i.e., review length) and imagery signal (i.e., number of pictures) instead of only examining them in isolation, and to examine whether these effects vary in different signaling environment (i.e., number of reviews associated with a product). By analyzing 4,063 online reviews of 39 Huawei mobile phones crawled from ZOL.com, this study empirically demonstrates that review helpfulness is positively influenced by both types of signals. Interestingly, the interaction between two types of signals has a negative impact on the perception of review helpfulness. The results also reveal that the signaling environment augments the impact of textual signal but mitigates the negative impact of the interaction between two types of signals on review helpfulness. The results of the study are anomalous to the established knowledge on consumer behaviors and possible explanations are presented. Based on these findings, both theoretical and practical implications are discussed.

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“…For avoiding potential multicollinearity among variables, all variables were mean centred before the interaction terms are created [61]. The estimated results are shown in Table IV.…”

Section: B Main Resultsmentioning

confidence: 99%

The Combination Signaling Effect of Text and Image on Mobile Phone Review Helpfulness - The Moderating Effect of Signaling Environment

Fan

Zhang

2020

IEEE Access

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“…The theoretical model developed in [38] shows that when the average rating of a product is low, the greater variance in ratings, the higher the sales of the product. A model is established to study how the early consumer's assessment of product value is passed to later stage consumers through consumer ratings; the results show that firms should choose different pricing strategies to maximize their profits based on whether consumers are able to observe the product's history price and market growth rate of the product [31]. The choice of whether or not to adopt an online review system as well as the optimal price should depend on the value and prevalence of the product [24].…”

Section: Dynamic Pricing In the Presence Of Online Consumer Reviewsmentioning

confidence: 99%

Pricing Strategies in Presence of Online Consumer Ratings - from the Product Customization Perspective

Tian

2020

J. theor. appl. electron. commer. res.

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Although there is abundant evidence that online consumer ratings have significant impacts on firms' pricing strategies, it is unclear how such impacts are influenced by the degree of product customization. This paper sets up a two-period dynamic model to analyze a firm's pricing strategies and the changes in its profitability when it sells products with different customization degrees (i.e., niche, neutral or mainstream). Consumers are uninformed of the product value. However, the first-period consumers generate online consumer ratings after their consumptions, and such ratings enable the second-period consumers to better understand the product value and thus to improve their purchasing decisions. Our results show that, in anticipation of the impacts of online consumer reviews, the firm should adjust its pricing strategy according to the customization degree of its product. In particular, for neutral products, the firm should lower its expected price in the second period comparing to its first period price, but for niche and mainstream products, the pricing adjustments over periods depend on the product value.

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“…These methods presented three regularization techniques: (1) add-one smoothing for handling singular terms, (2) sublinear scaling and (3) bias term for shrinking the ratios between term weights. As a more specific topic, Lee et al (2017) [29] showed how the entropy of the sentiments in the review texts characterized their influence and bias on the relationship between online word-of-mouth (WOM) and product sales.…”

Section: Related Workmentioning

confidence: 99%

Improving Seeded k-Means Clustering with Deviation- and Entropy-Based Term Weightings

Buatoom

Kongprawechnon

Theeramunkong

2020

IEICE Trans. Inf. & Syst.

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The outcome of document clustering depends on the scheme used to assign a weight to each term in a document. While recent works have tried to use distributions related to class to enhance the discrimination ability. It is worth exploring whether a deviation approach or an entropy approach is more effective. This paper presents a comparison between deviation-based distribution and entropy-based distribution as constraints in term weighting. In addition, their potential combinations are investigated to find optimal solutions in guiding the clustering process. In the experiments, the seeded k-means method is used for clustering, and the performances of deviation-based, entropy-based, and hybrid approaches, are analyzed using two English and one Thai text datasets. The result showed that the deviation-based distribution outperformed the entropy-based distribution, and a suitable combination of these distributions increases the clustering accuracy by 10%.

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The role of entropy of review text sentiments on online WOM and movie box office sales

Cited by 58 publications

References 51 publications

The Combination Signaling Effect of Text and Image on Mobile Phone Review Helpfulness - The Moderating Effect of Signaling Environment

The Combination Signaling Effect of Text and Image on Mobile Phone Review Helpfulness - The Moderating Effect of Signaling Environment

Pricing Strategies in Presence of Online Consumer Ratings - from the Product Customization Perspective

Improving Seeded k-Means Clustering with Deviation- and Entropy-Based Term Weightings

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