Are Consumers More Likely to Contribute Online Reviews for Hit or Niche Products?
User-generated content has been hailed by some as a democratizing force that enables consumers to discuss niche products that were previously ignored by mainstream media. Nevertheless, the extent to which consumers truly prefer to use these new outlets to discuss lesser-known products as opposed to spending most of their energies on discussing widely marketed or already successful products has so far remained an open question. We explore this question by investigating how a population's propensity to contribute postconsumption online reviews for different products of the same category (motion pictures) relates to various indicators of those products' popularity. We discover that, ceteris paribus, consumers prefer to post reviews for products that are less available and less successful in the market. At the same time, however, they are also more likely to contribute reviews for products that many other people have already commented on online. The presence of these two opposite forces leads to a U-shaped relationship between a population's average propensity to review a movie postconsumption and that movie's box office revenues: moviegoers appear to be more likely to contribute reviews for very obscure movies but also for very high-grossing movies. Our findings suggest that online forum designers who wish to increase the contribution of user reviews for lesser-known products should make information about the volume of previously posted reviews a less-prominent feature of their sites.
Available from: Wonjoon Kim
- "More specifically, using NLP, we are able to examine the proportion of emotional content in online product reviews across different star ratings and the distribution of emotional content in positive and negative product reviews as well as over time, which enables us to characterize unexplored characteristics of online WOM content. In addition, we also overcome the limitation of previous studies that focused on only a similar set of products, and examined the differences among customer reviews depending on product types (search vs. experience goods), which were considered to be open questions until now (Dellarocas et al., 2010; Duan et al., 2008a). "
Available from: Wonjoon Kim
- "More specifically, using NLP, we are able to examine the proportion of emotional content in online product reviews across different star ratings and the distribution of emotional content in positive and negative product reviews as well as over time, which enables us to characterize unexplored characteristics of online WOM content . In addition, we also overcome the limitation of previous studies that focused on only a similar set of products, by examining the differences among customer reviews depending on product types (search vs. experience goods), which were considered to be open questions until now  . "
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ABSTRACT: Word-of-mouth (WOM) in the form of online customer reviews has received considerable attention by practitioners and academics. Prior literature has focused more on the understanding of the phenomenon using the frequency or overall rating/valence information of WOM, while questions on how firms can potentially use or design online WOM platforms and benefit from it based on the content of WOM are still open, and needs more attention from researchers. In addition, an important antecedent for the generation of word-of-mouth is a strong emotional imbalance known as schema discrepancy, which is considered to trigger the consumer to post a customer review online. However, only a limited number of studies to date have actually examined the emotional content of reviews to validate this line of reasoning. To fill this gap, we analyzed the emotional content of a large number of online product reviews using Natural Language Processing (NLP) methods. We find that there is a difference in the emotional content of reviews between search and experience goods in the early stages of product launch. However, interestingly, these differences disappear over time as the addition of reviews reduces the information asymmetry gap. This suggests that traditional experience goods are evaluated more like search goods in online environments, because consumers can easily evaluate attributes of products prior to purchase based on the reviews accumulated. In addition, we find that more extreme reviews have a greater proportion of emotional content than less extreme reviews, revealing a bimodal distribution of emotional content, thereby empirically validating a key assumption that underpins much of the extant literature on online WOM. Furthermore, reviews have a greater proportion of positive emotional content within positive extreme ratings as compared to negative emotional content within negative extreme ratings which is a major factor in online WOM generation, and helps explain the commonly observed J-shaped distribution of reviews. Our findings suggest important managerial implications regarding product development, advertisement, and platform design using WOM content.
Available from: Scott D Swain
- "Recent research in the areas of information systems and marketing provides a number of insights on reviews. In terms of antecedents, studies identify the characteristics and motivations of those who write reviews   , including strategic fake reviews written on behalf of organizations  and non-strategic deceptive reviews written by individual, non-purchasers . Complementing this perspective, another stream of research examines the outcomes of reviews, finding that reviews affect aggregate consumer behavior as reflected in sales, profits, and viewership       , website and product evaluations    , competitive intelligence , and individual consumer choice   . "
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ABSTRACT: Many online retailers and other product-oriented websites allow people to post product reviews for use by shoppers. While research indicates that these reviews influence consumers' shopping attitudes and behaviors, questions remain about how consumers evaluate the product reviews themselves. With the current research, we introduce a new methodology for identifying the review factors that shoppers use to evaluate review helpfulness, and we integrate prior literature to provide a framework that explains how these factors reflect readers' general concerns about the diagnosticity (uncertainty and equivocality) and credibility (trust and expertise) of electronic word-of-mouth. Based on this framework, we offer predictions about how the relative importance of diagnosticity and credibility should vary systematically across search and experience product types. By analyzing secondary data consisting of over 8000 helpfulness ratings from product reviews posted by shoppers on Amazon.com, we find that, while review content affects helpfulness in complex ways, these effects are well explained by the proposed framework. Interestingly, the data suggest that review writers who explicitly attempt to enhance review diagnosticity or credibility are often ineffective or systematically unhelpful. Our findings have implications for both IS developers and retailers for designing online decision support systems to optimize communication practices and better manage consumer-generated content and interactions among consumers.
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