CoolFace
Datasetpublic

polinaeterna/amazon_us_reviews

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews. Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters). Each Dataset contains the following columns: - marketplace: 2 letter country code of the marketplace where the review was written. - customer_id: Random identifier that can be used to aggregate reviews written by a single author. - review_id: The unique ID of the review. - product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id. - product_parent: Random identifier that can be used to aggregate reviews for the same product. - product_title: Title of the product. - product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts). - star_rating: The 1-5 star rating of the review. - helpful_votes: Number of helpful votes. - total_votes: Number of total votes the review received. - vine: Review was written as part of the Vine program. - verified_purchase: The review is on a verified purchase. - review_headline: The title of the review. - review_body: The review text. - review_date: The date the review was written.

sourceHugging Faceotherupdated 3y agoView on Hugging Face
5likes727downloads
Dataset Card

Dataset Card for "amazonusreviews"

Table of Contents

Dataset Description

Dataset Summary

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews. Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters). Each Dataset contains the following columns : marketplace - 2 letter country code of the marketplace where the review was written. customerid - Random identifier that can be used to aggregate reviews written by a single author. reviewid - The unique ID of the review. productid - The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same productid. productparent - Random identifier that can be used to aggregate reviews for the same product. producttitle - Title of the product. productcategory - Broad product category that can be used to group reviews (also used to group the dataset into coherent parts). starrating - The 1-5 star rating of the review. helpfulvotes - Number of helpful votes. totalvotes - Number of total votes the review received. vine - Review was written as part of the Vine program. verifiedpurchase - The review is on a verified purchase. reviewheadline - The title of the review. reviewbody - The review text. reviewdate - The date the review was written.

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

Apparelv100
  • Size of downloaded dataset files: 648.64 MB
  • Size of the generated dataset: 2254.36 MB
  • Total amount of disk used: 2903.00 MB

An example of 'train' looks as follows.

{
    "customer_id": "45223824",
    "helpful_votes": 0,
    "marketplace": "US",
    "product_category": "Apparel",
    "product_id": "B016PUU3VO",
    "product_parent": "893588059",
    "product_title": "Fruit of the Loom Boys' A-Shirt (Pack of 4)",
    "review_body": "I ordered the same size as I ordered last time, and these shirts were much larger than the previous order. They were also about 6 inches longer. It was like they sent men's shirts instead of boys' shirts. I'll be returning these...",
    "review_date": "2015-01-01",
    "review_headline": "Sizes not correct, too big overall and WAY too long",
    "review_id": "R1N3Z13931J3O9",
    "star_rating": 2,
    "total_votes": 0,
    "verified_purchase": 1,
    "vine": 0
}
Automotivev100
  • Size of downloaded dataset files: 582.15 MB
  • Size of the generated dataset: 1518.88 MB
  • Total amount of disk used: 2101.03 MB

An example of 'train' looks as follows.

{
    "customer_id": "16825098",
    "helpful_votes": 0,
    "marketplace": "US",
    "product_category": "Automotive",
    "product_id": "B000E4PCGE",
    "product_parent": "694793259",
    "product_title": "00-03 NISSAN SENTRA MIRROR RH (PASSENGER SIDE), Power, Non-Heated (2000 00 2001 01 2002 02 2003 03) NS35ER 963015M000",
    "review_body": "Product was as described, new and a great look. Only bad thing is that one of the screws was stripped so I couldn't tighten all three.",
    "review_date": "2015-08-31",
    "review_headline": "new and a great look. Only bad thing is that one of ...",
    "review_id": "R2RUIDUMDKG7P",
    "star_rating": 3,
    "total_votes": 0,
    "verified_purchase": 1,
    "vine": 0
}
Babyv100
  • Size of downloaded dataset files: 357.40 MB
  • Size of the generated dataset: 956.30 MB
  • Total amount of disk used: 1313.70 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "customer_id": "23299101",
    "helpful_votes": 2,
    "marketplace": "US",
    "product_category": "Baby",
    "product_id": "B00SN6F9NG",
    "product_parent": "3470998",
    "product_title": "Rhoost Nail Clipper for Baby - Ergonomically Designed and Easy to Use Baby Nail Clipper, Natural Wooden Bamboo - Baby Health and Personal Care Kits",
    "review_body": "\"This is an absolute MUST item to have!  I was scared to death to clip my baby's nails.  I tried other baby nail clippers and th...",
    "review_date": "2015-08-31",
    "review_headline": "If fits so comfortably in my hand and I feel like I have ...",
    "review_id": "R2DRL5NRODVQ3Z",
    "star_rating": 5,
    "total_votes": 2,
    "verified_purchase": 1,
    "vine": 0
}
Beautyv100
  • Size of downloaded dataset files: 914.08 MB
  • Size of the generated dataset: 2397.39 MB
  • Total amount of disk used: 3311.47 MB

An example of 'train' looks as follows.

{
    "customer_id": "24655453",
    "helpful_votes": 1,
    "marketplace": "US",
    "product_category": "Beauty",
    "product_id": "B00SAQ9DZY",
    "product_parent": "292127037",
    "product_title": "12 New, High Quality, Amber 2 ml (5/8 Dram) Glass Bottles, with Orifice Reducer and Black Cap.",
    "review_body": "These are great for small mixtures for EO's, especially for traveling.  I only gave this 4 stars because of the orifice reducer.  The hole is so small it is hard to get the oil out.  Just needs to be slightly bigger.",
    "review_date": "2015-08-31",
    "review_headline": "Good Product",
    "review_id": "R2A30ALEGLMCGN",
    "star_rating": 4,
    "total_votes": 1,
    "verified_purchase": 1,
    "vine": 0
}
Booksv100
  • Size of downloaded dataset files: 2740.34 MB
  • Size of the generated dataset: 7193.86 MB
  • Total amount of disk used: 9934.20 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "customer_id": "49735028",
    "helpful_votes": 0,
    "marketplace": "US",
    "product_category": "Books",
    "product_id": "0664254969",
    "product_parent": "248307276",
    "product_title": "Presbyterian Creeds: A Guide to the Book of Confessions",
    "review_body": "\"The Presbyterian Book of Confessions contains multiple Creeds for use by the denomination. This guidebook helps he lay person t...",
    "review_date": "2015-08-31",
    "review_headline": "The Presbyterian Book of Confessions contains multiple Creeds for use ...",
    "review_id": "R2G519UREHRO8M",
    "star_rating": 3,
    "total_votes": 1,
    "verified_purchase": 1,
    "vine": 0
}

Data Fields

The data fields are the same among all splits.

Apparelv100
  • marketplace: a string feature.
  • customer_id: a string feature.
  • review_id: a string feature.
  • product_id: a string feature.
  • product_parent: a string feature.
  • product_title: a string feature.
  • product_category: a string feature.
  • star_rating: a int32 feature.
  • helpful_votes: a int32 feature.
  • total_votes: a int32 feature.
  • vine: a classification label, with possible values including Y (0), N (1).
  • verified_purchase: a classification label, with possible values including Y (0), N (1).
  • review_headline: a string feature.
  • review_body: a string feature.
  • review_date: a string feature.
Automotivev100
  • marketplace: a string feature.
  • customer_id: a string feature.
  • review_id: a string feature.
  • product_id: a string feature.
  • product_parent: a string feature.
  • product_title: a string feature.
  • product_category: a string feature.
  • star_rating: a int32 feature.
  • helpful_votes: a int32 feature.
  • total_votes: a int32 feature.
  • vine: a classification label, with possible values including Y (0), N (1).
  • verified_purchase: a classification label, with possible values including Y (0), N (1).
  • review_headline: a string feature.
  • review_body: a string feature.
  • review_date: a string feature.
Babyv100
  • marketplace: a string feature.
  • customer_id: a string feature.
  • review_id: a string feature.
  • product_id: a string feature.
  • product_parent: a string feature.
  • product_title: a string feature.
  • product_category: a string feature.
  • star_rating: a int32 feature.
  • helpful_votes: a int32 feature.
  • total_votes: a int32 feature.
  • vine: a classification label, with possible values including Y (0), N (1).
  • verified_purchase: a classification label, with possible values including Y (0), N (1).
  • review_headline: a string feature.
  • review_body: a string feature.
  • review_date: a string feature.
Beautyv100
  • marketplace: a string feature.
  • customer_id: a string feature.
  • review_id: a string feature.
  • product_id: a string feature.
  • product_parent: a string feature.
  • product_title: a string feature.
  • product_category: a string feature.
  • star_rating: a int32 feature.
  • helpful_votes: a int32 feature.
  • total_votes: a int32 feature.
  • vine: a classification label, with possible values including Y (0), N (1).
  • verified_purchase: a classification label, with possible values including Y (0), N (1).
  • review_headline: a string feature.
  • review_body: a string feature.
  • review_date: a string feature.
Booksv100
  • marketplace: a string feature.
  • customer_id: a string feature.
  • review_id: a string feature.
  • product_id: a string feature.
  • product_parent: a string feature.
  • product_title: a string feature.
  • product_category: a string feature.
  • star_rating: a int32 feature.
  • helpful_votes: a int32 feature.
  • total_votes: a int32 feature.
  • vine: a classification label, with possible values including Y (0), N (1).
  • verified_purchase: a classification label, with possible values including Y (0), N (1).
  • review_headline: a string feature.
  • review_body: a string feature.
  • review_date: a string feature.

Data Splits

nametrain
Apparelv1005906333
Automotivev1003514942
Babyv1001752932
Beautyv1005115666
Booksv10010319090
Booksv1016106719
Booksv1023105520
Camerav1001801974
DigitalEbookPurchasev10012520722
DigitalEbookPurchasev1015101693
DigitalMusicPurchasev1001688884
DigitalSoftwarev1_00102084
DigitalVideoDownloadv1004057147
DigitalVideoGamesv100145431
Electronicsv1003093869
Furniturev100792113
GiftCardv1_00149086
Groceryv1002402458
HealthPersonalCarev1005331449
HomeEntertainmentv1_00705889
HomeImprovementv1_002634781
Homev1006221559
Jewelryv1001767753
Kitchenv1004880466
LawnandGardenv1002557288
Luggagev100348657
MajorAppliancesv1_0096901
MobileAppsv1_005033376
MobileElectronicsv1_00104975
Musicv1004751577
MusicalInstrumentsv1_00904765
OfficeProductsv1_002642434
Outdoorsv1002302401
PCv1006908554
PersonalCareAppliancesv10085981
PetProductsv1_002643619
Shoesv1004366916
Softwarev100341931
Sportsv1004850360
Toolsv1001741100
Toysv1004864249
VideoDVDv1_005069140
VideoGamesv1_001785997
Videov100380604
Watchesv100960872
Wirelessv1009002021

Dataset Creation

Curation Rationale

More Information Needed

Source Data

Initial Data Collection and Normalization

More Information Needed

Who are the source language producers?

More Information Needed

Annotations

Annotation process

More Information Needed

Who are the annotators?

More Information Needed

Personal and Sensitive Information

More Information Needed

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

More Information Needed

Other Known Limitations

More Information Needed

Additional Information

Dataset Curators

More Information Needed

Licensing Information

https://s3.amazonaws.com/amazon-reviews-pds/LICENSE.txt

By accessing the Amazon Customer Reviews Library ("Reviews Library"), you agree that the Reviews Library is an Amazon Service subject to the Amazon.com Conditions of Use and you agree to be bound by them, with the following additional conditions:

In addition to the license rights granted under the Conditions of Use, Amazon or its content providers grant you a limited, non-exclusive, non-transferable, non-sublicensable, revocable license to access and use the Reviews Library for purposes of academic research. You may not resell, republish, or make any commercial use of the Reviews Library or its contents, including use of the Reviews Library for commercial research, such as research related to a funding or consultancy contract, internship, or other relationship in which the results are provided for a fee or delivered to a for-profit organization. You may not (a) link or associate content in the Reviews Library with any personal information (including Amazon customer accounts), or (b) attempt to determine the identity of the author of any content in the Reviews Library. If you violate any of the foregoing conditions, your license to access and use the Reviews Library will automatically terminate without prejudice to any of the other rights or remedies Amazon may have.

Citation Information

No citation information.

Contributions

Thanks to @joeddav for adding this dataset.