Recipe Reviews and User Feedback

Donated on 10/23/2023

The "Recipe Reviews and User Feedback Dataset" is a comprehensive repository of data encompassing various aspects of recipe reviews and user interactions. It includes essential information such as the recipe name, its ranking on the top 100 recipes list, a unique recipe code, and user details like user ID, user name, and an internal user reputation score. Each review comment is uniquely identified with a comment ID and comes with additional attributes, including the creation timestamp, reply count, and the number of up-votes and down-votes received. Users' sentiment towards recipes is quantified on a 1 to 5 star rating scale, with a score of 0 denoting an absence of rating. This dataset is a valuable resource for researchers and data scientists, facilitating endeavors in sentiment analysis, user behavior analysis, recipe recommendation systems, and more. It offers a window into the dynamics of recipe reviews and user feedback within the culinary website domain.

Dataset Characteristics

Tabular, Other

Subject Area

Computer Science

Associated Tasks

Classification, Other

Feature Type

Real, Categorical, Integer

# Instances


# Features


Dataset Information

Has Missing Values?

Yes (symbol: 2)

Introductory Paper

Textual Taste Buds: A Profound Exploration of Emotion Identification in Food Recipes through BERT and AttBiRNN Models

By Amir Ali, Stanislaw Matuszewski, Jacek Czupyt, Usman Ahmad. 2023

Published in International Journal of Novel Research and Development

Variables Table

Variable NameRoleTypeDescriptionUnitsMissing Values
num_recordsFeatureIntegernumber of recordsno
recipe_numberFeatureIntegerplacement of the recipe on the top 100 recipes listno
recipe_codeFeatureIntegerunique id of the recipe used by the siteno
recipe_nameFeatureCategoricalname of the recipe the comment was posted onno
comment_idFeatureCategoricalunique id of the commentno
user_idFeatureCategoricalunique id of the user who left he commentno
user_nameFeatureCategoricalname of the userno
user_reputationFeatureIntegerinternal score of the site, roughly roughly quantifying the past behaviour of the userno
created_atFeatureIntegertime at which the comment was posted as unix timestamp no
reply_countFeatureIntegernumber of replies to the commentno

0 to 10 of 15

Additional Variable Information

1. recipe name: {name of the recipe the comment was posted on} 2. recipe number: {placement of the recipe on the top 100 recipes list} 3. recipe code: {unique id of the recipe used by the site} 4. comment id: {unique id of the comment} 5. user id: {unique id of the user who left the comment} 6. user name: {name of the user} 7. user reputation: {internal score of the site, roughly quantifying the past behavior of the user} 8. create at: {time at which the comment was posted as a Unix timestamp} 9. reply count: {number of replies to the comment} 10. thumbs up: {number of up-votes the comment has received} 11. thumbs down: {number of down-votes the comment has received} 12. stars: {the score on a 1 to 5 scale that the user gave to the recipe. A score of 0 means that no score was given} 13. best score: {score of the comment, likely used by the site the help determine the order in the comments that appear in} 14. text: {the text content of the comment}


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1 citations


Text classificationSentiment analysis


Amir Ali

Warsaw University of Technology

Stanislaw Matuszewski

Warsaw University of Technology

Jacek Czupyt

Warsaw University of Technology


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