It has been established in the literature that the number of ratings and the scores restaurants obtain on online rating systems (ORS) significantly impact their revenue. However, when a restaurant has a limited number of ratings, it may be challenging to predict its future performance. It may well be that ratings reveal more about the user who did the rating than about the quality of the restaurant. This motivates us to segment users into "inflating raters", who tend to give unusually high ratings, and "deflating raters", who tend to give unusually low ratings, and compare the rankings generated by these two populations. Using a public dataset provided by Yelp, we find that deflating raters are better at predicting restaurants that will achieve a top rating (4.5 and above) in the future. As such, these deflating raters may have an important role in restaurant discovery.

翻译：文献已证实，在线评分系统中餐馆获得的评分数量及分数对其收入有显著影响。然而，当一家餐馆的评分数量有限时，预测其未来表现可能具有挑战性。评分可能更多地反映评分者的个人偏好，而非餐馆的实际质量。这促使我们将用户分为“高估评分者”（倾向于给出异常高分）和“低估评分者”（倾向于给出异常低分），并比较这两类群体产生的排名。利用Yelp提供的公开数据集，我们发现低估评分者在预测未来达到顶级评分（4.5分及以上）的餐馆方面表现更优。因此，这些低估评分者可能在餐馆发现过程中发挥重要作用。