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Yelp-dataset-samples

A sample dataset of 1001 Yelp business reviews

Yelp dataset header

A Yelp dataset sample of over 1000 Yelp business reviews. Dataset was extracted using the Bright Data API.

Some of the data points that are included in the dataset:

  • business_id: A unique identifier for the business
  • Review_author: The author or user who wrote the review
  • Rating: The rating given by the reviewer
  • Date: The date when the review was posted
  • Content: The textual content of the review
  • Review_image: An image associated with the review
  • Reactions: Reactions received from other users on the review
  • Replies: Replies or responses to the review
  • review_order: The order or sequence of the review among others for the same business
  • Elite_status: Indicates whether the author of the review has elite status

And a lot more.

This is a sample subset which is derived from the "Yelp business reviews" dataset which includes more than 200M records.

Available dataset file formats: JSON, NDJSON, JSON Lines, CSV, or Parquet. Optionally, files can be compressed to .gz.

Dataset delivery type options: Email, API download, Webhook, Amazon S3, Google Cloud storage, Google Cloud PubSub, Microsoft Azure, Snowflake, SFTP.

Update frequency: Once, Daily, Weekly, Monthly, Quarterly, or Custom basis.

Data enrichment available as an addition to the data points extracted: Based on request.

Get the full Yelp dataset.

What are the Yelp datasets use cases?

1. Consumer Sentiment Analysis

Gain insights into customer feedback by analyzing reviews and comments on your business, competitors, and industry trends. Use this analysis to enhance product offerings, improve services, and personalize the customer experience. This allows you to respond proactively to customer needs and stay competitive.

2. Market Research and Growth Opportunities

Monitor shifts in business locations, ratings, and customer reviews to identify emerging market trends and potential areas for expansion. By staying updated on industry changes, you can proactively spot growth opportunities and make data-driven decisions to strengthen your market position.

3. Competitor Analysis Using B2B Data

Gather data on competitor businesses, such as restaurants, home services, and auto services, to analyze their operating hours, locations, customer reviews, and service offerings. Leveraging this data enables a deeper understanding of competitors' strengths and weaknesses, allowing you to refine your strategies and improve your own business positioning.

Free access to web scraping tools and datasets for academic researchers and NGOs

The Bright Initiative offers access to Bright Data's Web Scraper APIs and ready-to-use datasets to leading academic faculties and researchers, NGOs and NPOs promoting various environmental and social causes. You can submit an application here.