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Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud

机译:直到您成功为止都是假的:声誉,竞争和Yelp审查欺诈

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摘要

Consumer reviews are now part of everyday decision making. Yet the credibility of these reviews is fundamentally undermined when businesses commit review fraud, creating fake reviews for themselves or their competitors. We investigate the economic incentives to commit review fraud on the popular review platform Yelp, using two complementary approaches and data sets. We begin by analyzing restaurant reviews that are identified by Yelp's filtering algorithm as suspicious, or fake-and treat these as a proxy for review fraud (an assumption we provide evidence for). We present four main findings. First, roughly 16% of restaurant reviews on Yelp are filtered. These reviews tend to be more extreme (favorable or unfavorable) than other reviews, and the prevalence of suspicious reviews has grown significantly over time. Second, a restaurant is more likely to commit review fraud when its reputation is weak, i.e., when it has few reviews or it has recently received bad reviews. Third, chain restaurants-which benefit less from Yelp-are also less likely to commit review fraud. Fourth, when restaurants face increased competition, they become more likely to receive unfavorable fake reviews. Using a separate data set, we analyze businesses that were caught soliciting fake reviews through a sting conducted by Yelp. These data support our main results and shed further light on the economic incentives behind a business's decision to leave fake reviews.
机译:消费者评论现已成为日常决策的一部分。但是,当企业进行审查欺诈,为自己或竞争对手创建虚假审查时,这些审查的信誉就会从根本上受到损害。我们使用两种互补的方法和数据集,对在流行的评论平台Yelp上进行评论欺诈的经济动机进行了调查。我们首先分析由Yelp的过滤算法识别为可疑或伪造的餐厅评论,然后将其视为评论欺诈的代理(我们提供证据的假设)。我们提出了四个主要发现。首先,大约有16%的Yelp餐厅评论被过滤掉了。这些评论往往比其他评论更为极端(有利或不利),并且随着时间的推移,可疑评论的流行率已显着增长。其次,在餐厅声誉不佳(即评论很少或最近收到不良评论)时,餐厅更有可能犯下评论欺诈行为。第三,从Yelp受益较少的连锁餐厅也不太可能犯下审查欺诈罪。第四,当餐馆面临竞争加剧时,他们更有可能收到不利的虚假评论。使用单独的数据集,我们通过Yelp进行的分析来分析被诱骗假评论的企业。这些数据支持了我们的主要结果,并进一步阐明了企业决定放弃假评论的经济动机。

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