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Recipe User Feedback
Reviews & Ratings
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset provides a detailed collection of user interactions and recipe reviews from culinary websites. It is designed to offer insights into the dynamics of user-generated content and opinions within the food and recipe industry. The data includes specific details about recipes and their performance, along with user information and various metrics related to comment engagement, such as upvotes, downvotes, and response counts. It serves as a valuable resource for understanding user behaviour and sentiment around culinary content.
Columns
- rec_no: Indicates the recipe's ranking within the top 100 recipes listed on the website.
- rec_cd: A distinct identifier used by the website for each recipe.
- rec_nm: The name of the recipe being reviewed.
- cmt_id: A unique identification for each comment posted.
- user_id: The individual identifier for the user who made the comment.
- user_nm: The name associated with the user who posted the comment.
- user_reput: An internal site score that provides an approximate measure of the user's past behaviour and standing on the platform.
- timestamp: A Unix timestamp marking the exact moment the comment was posted.
- response_no: The total number of replies or responses a comment has received.
- upvotes: The count of positive votes or 'upvotes' given to the comment.
- downvotes: The count of negative votes or 'downvotes' received by the comment.
- ratings: The user's star rating for the recipe, ranging from 1 to 5, where 0 signifies no evaluation was provided.
- max_rating: A score attributed to the comment, likely utilised by the website to influence the display order of comments.
- comment: The actual text content of the user's review comment.
Distribution
The dataset is structured for near-real-time monitoring of user and recipe reviews. It contains approximately 18,182 records. For instance, the user reputation scores are distributed across various ranges, with the largest count (2,423) falling between 1.00 and 5.95. Response counts for comments predominantly fall within the 0.00 - 26.00 range, accounting for 18,029 instances, while unique response numbers total 18,182. Similarly, upvotes are largely in the 0.00 - 5.30 range (17,208 instances), with 13,812 unique upvote counts. Downvotes show a pattern where most comments (17,952) have between 0.00 and 0.15 downvotes, and there are 13,586 unique downvote counts. The timestamps span from approximately 1.61 billion to 1.67 billion Unix time, indicating a collection period over several years.
Usage
This dataset is ideally suited for various analytical applications, including:
- Sentiment analysis: To gauge public opinion and emotional tone expressed in recipe reviews.
- User behaviour analysis: To understand how users interact with culinary content and each other.
- Recipe recommendation systems: To develop algorithms that suggest recipes based on user preferences and review patterns.
Coverage
The data originates from user reviews and recipe reviews on websites related to the culinary industry. It covers a global scope and includes user details such as IDs, names, and reputation scores, offering insights into their interactions. The time range for the comment timestamps extends from roughly March 2021 to October 2022 (based on Unix timestamp conversions), providing a recent view of user activity.
License
CC-BY
Who Can Use It
This dataset is particularly valuable for:
- Researchers: For academic studies on online communities, consumer behaviour, or text analytics.
- Data scientists: To build predictive models, recommendation engines, or sentiment classifiers.
- Anyone interested in the dynamics of user reviews and recipe performance in the culinary domain.
Dataset Name Suggestions
- Culinary Review Dataset
- Recipe User Feedback
- Online Food Review Data
- User-Generated Recipe Insights
- Digital Cookbook Reviews
Attributes
Original Data Source: 🍲 Cookbook Reviews 🍝 : Sentiment Analysis
QUALITY