The Anatomy of Online Reviews: Evidence from the Steam Store

现在，在线评论已经成为现代消费者信息的一部分。但对于消费者来说，评论作为产品质量的信号有多好呢？我使用一个来自流行的“蒸汽”游戏平台的数据集，调查了评论生成过程中的两个相互关联的问题：评价者的自我选择和基于先前存在的消费者评估的质量判断的“启动”。2019年关于蒸汽的政策改革既降低了审查的交易成本，又改变了对先前存在的消费者质量评级的平均敞口水平，这是在游戏和评论者的生命周期中随机发生的。我发现，政策变化引发的新个人对任何游戏给予正面评价的可能性增加了4%，对任何游戏的评论时间缩短了20%，在游戏内部和游戏之间的经验都较少。此外，减少评审者对产品平均评级的暴露会导致他们的评审对此类评级的依赖程度大幅下降。这种影响是不对称的，评分越低的游戏得到的好评越多，这表明负面意见可能会复合在一起，导致评分下降。总体而言，这项政策导致了一款游戏的评分更好地反映了它在玩家中的受欢迎程度，但这些新的评论者被同行评为帮助较小，这意味着更准确的评论分数是以帮助较少的评论为代价的。

Online reviews are now a ubiquitous part of the modern consumer's information set. But how good are reviews as signals of product quality for consumers? Using a dataset derived from the popular `Steam' gaming platform I investigate two linked issues in the generation of reviews: the self-selection of reviewers and the `priming' of quality judgements as based on pre-existing consumer assessments. A policy reform on Steam in 2019 both lowered the transaction cost of reviewing and changed the average level of exposure to pre-existing consumer quality ratings, and this randomly occured within a game and reviewer's life cycle. I find that the new individuals elicited to review by the policy change are 4% more likely to rate any game positively, leave 20% shorter reviews and are less experienced both within and across games. In addition, reducing the exposure of a reviewer to a product's average rating leads to a substantive drop in the dependency of their review on such a rating. This effect is asymmetric, with worse-rated games receiving more positive reviews, suggesting that negative opinions can compound to bias ratings downward. Overall, the policy led to a game's rating better reflecting its popularity with players, but these new reviewers were rated as less helpful by their peers, implying that more accurate review scores come at the cost of less helpful reviews.