Rating the online review rating system using Yelp

TL;DR

This paper analyzes Yelp restaurant ratings to identify biases caused by location and features, aiming to develop an optimized global rating system that accounts for these discrepancies.

Contribution

It investigates the influence of restaurant features and location on ratings, proposing adjustments to improve rating accuracy beyond subjective individual perspectives.

Findings

Ratings are biased by location and amenities.

Discrepancies are influenced by restaurant features and individual perceptions.

Proposes a method to normalize ratings for better comparability.

Abstract

The impact of ratings on a restaurant plays a major role in attracting future customers to that restaurant. The word of mouth has been systematically replaced with the online reviews. It gives a sense of satisfaction for people to know beforehand about the number of average stars the restaurant has acquired before stepping into a restaurant. However, these ratings are indirectly biased based on the location, amenities, and the perception of individual people. In this work, we analyze the ratings of restaurants available through the Yelp public data for the discrepancies in the rating system and attempt to provide an optimized global rating system. For a frequent visitor to a high- end restaurant with lavish amenities, even a slightest of reduction in the expected ambiance may prompt a 4 star rating, while a restaurant, which guarantees a minimum taste for its food, may get a 5 star rating. These discrepancies can often be attributed to three factors- the perspective of individual people, features of the restaurant and Location. The perspective of individual people is always subjective and what seems good for one person may be poor for another. In this work, we focus on the other two important factors, Reviews and the features.