Born Unequal: A Study of the Helpfulness of User-Generated Product Reviews

By Yue Pan, Jason Q. Zhang. 2011

660 citations recorded by the source corpus.

Subfields: Information Systems and Management, Marketing, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/f6273d98255af9a025380ff910d09d7f217b4434

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Citations in the corpus

Consumer perceptions of information helpfulness and determinants of purchase intention in online consumer reviews of services (2018, background): “focused on review text characteristics adopted datasets of customer reviews from e-tailers, measuring review length, readability, and linguistic correctness [4, 16, 30, 38, 52, 54, 59, 62].”
Research Note - When Do Consumers Value Positive vs. Negative Reviews? An Empirical Investigation of Confirmation Bias in Online Word of Mouth (2015, background): “Thus, the positive–negative asymmetry often studied in the literature can be a consequence of confirmation bias (for similar arguments, see Pan and Zhang (2011).”
A big data exploration of the informational and normative influences on the helpfulness of online restaurant reviews (2021, result): “Whereas, in direct contrast to these findings, Pan and Zhang (2011) observed a positivity bias in the relationship between review valence (star rating) and helpfulness, emphasising that positivity levels are heightened for experience goods.”
Extremely Negative Ratings and Online Consumer Review Helpfulness: The Moderating Role of Product Quality Signals (2020, background): “Moreover, the discussion around the factors that influence the helpfulness of online consumer reviews the most is broadening (Filieri 2015; Kwok and Xie 2016; Mudambi and Schuff 2010; Pan and Zhang 2011; S. Park and Nicolau 2015; M. Lee et al. 2017; Shin et al. 2019; Wang, Tang, and Kim 2019).”
Importance of Online Product Reviews from a Consumer's Perspective (2013, background): “Another study of Pan and Zhang [3] showed that the perceived helpfulness of a review positively correlates with the length of the review, which means that a long review text is usually more helpful than a short review text.”
Does Twitter matter? The impact of microblogging word of mouth on consumers’ adoption of new movies (2014, positive): “Pan and Zhang (2011) suggest that the length of EWOM reviews increases perceived helpfulness.”
Helpfulness of Online Product Reviews as Seen by Consumers: Source and Content Features (2013, methodology): “For instance, Mudambi and Schuff (2010) connect the review helpfulness to the review diagnosticity [51], while Pan and Zhang [53] argue that the helpfulness can be used interchangeably with review usefulness.”
Assisting consumers in detecting fake reviews: The role of identity information disclosure and consensus (2016, background): “Recent findings that confirmed the role of review characteristics such as review length (Pan and Zhang, 2011, , see results of the preliminary study in the present research), word use (Ott et al., 2011), and word duplication (Bhattarai, Rus and Dasgupta, 2009) on consumers’ perceptions and the…”
Compliance with eWOM: the influence of hotel reviews on booking intention from the perspective of consumer conformity. (2015, background): “As a result, eWOM exerts greater and wider influence than traditional WOM (Pan and Zhang, 2011).”