User Reviews Variance, Critic Reviews Variance, and Product Sales: An Exploration of Customer Breadth and Depth Effects

Wang, Feng; Liu, Xuefeng; Fang, Eric

doi:10.1016/j.jretai.2015.04.007

Cited by 102 publications

(107 citation statements)

References 68 publications

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“…Some research on eWOM has shown mixed findings regarding the direct effects of eWOM on product sales [15,16]. Other research shows the moderating effects of rating variance [17], review helpfulness [18], and the features of reviewers [19], products [20,21], and social media platforms [22][23][24]. In this paper, we focus on the direct effects of eWOM.…”

Section: Ewom's Effect On Salesmentioning

confidence: 99%

“…Third, we set the dummy variable v t,4 to one if the day was on the weekend and zero otherwise to consider the seasonal effect. Fourth, the variable v t,5 represents the number of cinemas at which a film was being shown [17]. Finally, we used the Google Trends of movie names, and the initial trends range from 0 to 100 in terms of online search data.…”

Section: Data Collectionmentioning

confidence: 99%

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Sales Prediction by Integrating the Heat and Sentiments of Product Dimensions

et al. 2019

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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 dimensions from big data on eWOM. Ultimately, we propose an autoregressive heat-sentiment (ARHS) model that integrates the heat and sentiments of dimensions into the benchmark predictive model to forecast daily sales. We conduct an empirical study of the movie industry and confirm that the ARHS model is better than other models in predicting movie box-office revenues. The robustness check with regard to predicting opening-week revenues based on a back-propagation neural network also suggests that the heat and sentiments of dimensions can improve the accuracy of sales predictions when the machine-learning method is used.

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Section: Ewom's Effect On Salesmentioning

confidence: 99%

Section: Data Collectionmentioning

confidence: 99%

Sales Prediction by Integrating the Heat and Sentiments of Product Dimensions

et al. 2019

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“…Online Reviews. Previous work on online reviews focused on their rating and textual valence, as well as economical impact in sales of books [9,12,26], movies [18,24,26,29,33,61,70], restaurants [30,45] and video games [11,21,74,75]. As these works establish the existence and strength of a relationship between review characteristics and market performance of experience goods [54], we turn our attention to another indicator of public reception of video games in particular: the interplay between expert and amateur review ratings and texts.…”

Section: Related Workmentioning

confidence: 99%

What's in a Review

Santos

Lemmerich

Strohmaier

et al. 2019

Proc. ACM Hum.-Comput. Interact.

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As video game press ("experts") and casual gamers ("amateurs") have different motivations when writing video game reviews, discrepancies in their reviews may arise. To study such potential discrepancies, we conduct a large-scale investigation of more than 1 million reviews on the Metacritic review platform. In particular, we assess the existence and nature of discrepancies in video game appraisal by experts and amateurs, and how they manifest in ratings, over time, and in review language. Leveraging these insights, we explore the predictive power of early expert vs. amateur reviews in forecasting video game reputation in the short-and long-term. We find that amateurs, in contrast to experts, give more polarized ratings of video games, rate games surprisingly long after game release, and are positively biased towards older games. On a textual level, we observe that experts write rather complex, less readable texts than amateurs, whose reviews are more emotionally charged. While in the short-term amateur reviews are remarkably predictive of game reputation among other amateurs (achieving 91% ROC AUC in a binary classification), both expert and amateur reviews are equally well suited for long-term predictions. Overall, our work is the first large-scale comparative study of video game reviewing behavior, with practical implications for amateurs when deciding which games to play, and for game developers when planning which games to design, develop, or continuously support. More broadly, our work contributes to the discussion of wisdom of the few vs. wisdom of the crowds, as we uncover the limits of experts in capturing the views of amateurs in the particular context of video game reviews.

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“…It is described as a consumer purchasing decision. Wang et al, (2015), stated that customer review did not significantly affect purchasing decisions.…”

Section: Introductionmentioning

confidence: 99%

Community-based tourism: measuring readiness of artificial intelligence on traditional village

Astuti¹,

Darma²

2019

IJSSH

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The paper aimed at describing and elaborating the different meanings appear on the description of tourist destinations in two forms. On the one hand is a cyberspace image in two locations tourist destinations, on the other hand, is an image of the real fact after visitor came to a destination place. The research is as the basis of this paper combines two analyses. First, take and analyze the contents from review Trip Advisor and retrieve analytical data from the source www.social-searcher.com. Second, make observations and in-depth interviews of informants who came and witnessed a place of tourist destinations after getting information on digital pages. The analysis of the combined two data attempts to show the uniqueness, the gap, and the difference between cyberspace images of tourist destinations, with the opinions and perceptions of tourist visitors who have seen the real destination. The main aim of this article is to demonstrate the theoretical support of a model about the effect of digital marketing tools technologies on low-density tourism region. In order to achieve this purpose, a literature review will be used as a methodological basis.

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User Reviews Variance, Critic Reviews Variance, and Product Sales: An Exploration of Customer Breadth and Depth Effects

Cited by 102 publications

References 68 publications

Sales Prediction by Integrating the Heat and Sentiments of Product Dimensions

Sales Prediction by Integrating the Heat and Sentiments of Product Dimensions

What's in a Review

Community-based tourism: measuring readiness of artificial intelligence on traditional village

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