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
18182
# Features
15
Dataset Information
Has Missing Values?
Yes (symbol: 2)
Introductory Paper
By Amir Ali, Stanislaw Matuszewski, Jacek Czupyt, Usman Ahmad. 2023
Published in International Journal of Novel Research and Development
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
|---|---|---|---|---|---|
| num_records | Feature | Integer | number of records | no | |
| recipe_number | Feature | Integer | placement of the recipe on the top 100 recipes list | no | |
| recipe_code | Feature | Integer | unique id of the recipe used by the site | no | |
| recipe_name | Feature | Categorical | name of the recipe the comment was posted on | no | |
| comment_id | Feature | Categorical | unique id of the comment | no | |
| user_id | Feature | Categorical | unique id of the user who left he comment | no | |
| user_name | Feature | Categorical | name of the user | no | |
| user_reputation | Feature | Integer | internal score of the site, roughly roughly quantifying the past behaviour of the user | no | |
| created_at | Feature | Integer | time at which the comment was posted as unix timestamp | no | |
| reply_count | Feature | Integer | number of replies to the comment | no |
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}
Reviews
There are no reviews for this dataset yet.
pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset recipe_reviews_and_user_feedback = fetch_ucirepo(id=911) # data (as pandas dataframes) X = recipe_reviews_and_user_feedback.data.features y = recipe_reviews_and_user_feedback.data.targets # metadata print(recipe_reviews_and_user_feedback.metadata) # variable information print(recipe_reviews_and_user_feedback.variables)
Ali,Amir, Matuszewski,Stanislaw , and Czupyt,Jacek. (2023). Recipe Reviews and User Feedback. UCI Machine Learning Repository. https://doi.org/10.24432/C5FG95.
@misc{misc_recipe_reviews_and_user_feedback_911,
author = {Ali,Amir, Matuszewski,Stanislaw , and Czupyt,Jacek},
title = {{Recipe Reviews and User Feedback}},
year = {2023},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: https://doi.org/10.24432/C5FG95}
}Keywords
Creators
Amir Ali
amir.datascience@gmail.com
Warsaw University of Technology
Stanislaw Matuszewski
stanislaus.matuszewski@gmail.com
Warsaw University of Technology
Jacek Czupyt
jacek.czupyt@gmail.com
Warsaw University of Technology
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.