2010
DOI: 10.1016/j.intmar.2010.04.001
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The Differential Effects of Online Word-of-Mouth and Critics’ Reviews on Pre-release Movie Evaluation

Abstract: In this paper, we examine the persuasive influences of online user comments (or word-of-mouth) and of the reviews by movie critics on moviegoers’ evaluation of to-be-released movies. Two distinctive features of this study are: (1) moviegoers are considered to be heterogeneous in their movie going frequency and (2) word-of-mouth and critical reviews are concurrently available, and the views expressed in the two messages are in conflict. Using three experiments with natural stimuli, we find that the persuasive e… Show more

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Cited by 192 publications
(132 citation statements)
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References 58 publications
(56 reference statements)
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“…Research on WOM has reported differential effects for positive and negative WOM, predominantly finding that negative WOM is more influential (e.g., Chakravarty, Liu, and Mazumdar 2010). If MWOM valence matters, does such a "negativity bias" also exist for MWOM?…”
Section: Differential Effects For Positive and Negative Mwommentioning
confidence: 99%
“…Research on WOM has reported differential effects for positive and negative WOM, predominantly finding that negative WOM is more influential (e.g., Chakravarty, Liu, and Mazumdar 2010). If MWOM valence matters, does such a "negativity bias" also exist for MWOM?…”
Section: Differential Effects For Positive and Negative Mwommentioning
confidence: 99%
“…Furthermore, Ito et al (1998) have posited that positive information may not have a significant impact on evaluations in comparison to negative information. This is why in the decision-making process negative information ultimately trumps positive information in terms of influence A case study on how movies are evaluated based upon the type of e-UGC has shown that positive e-UGC has considerably less influence on end evaluations of the movies compared to negative e-UGC (Chakravarty et al, 2010). Individuals, particularly those that are not frequent moviegoers are still affected by negative e-UGC even in the presence of positive reviews given by movie critics (ibid.).…”
Section: Percentage Of Negative Online Reviewsmentioning
confidence: 99%
“…One noticeable advance is that almost any Internet user can contribute content to many websites (Chakravarty, Liu, & Mazumdar, 2010;Walther & Jang, 2012). For example, the eBay (www.ebay.com) and Amazon (www.amazon.com) reputation systems allow a buyer to leave comments about the seller after a transaction.…”
Section: Influence Of Online Comments On Readers' Perceptionsmentioning
confidence: 99%