Amazon QA — Pet Supplies

A Amazon dataset of 36,607 QA pairs in Pet Supplies, collected by Wan and McAuley via Amazon API. Each record contains question, answer, question type, answer type, ASIN, timestamp. Amazon product Q&A data for Pet Supplies. Suitable for question answering, sentiment analysis, product understanding, conversational AI.

#Asin#Pet supply#Product question answering

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Analytics

Content metrics

36,607 records scored · min–maxmean ± 0.675 σ (the interquartile range if the values are roughly normal)mean

unixTimeμ 1.3B ± 268.4M
min 0max 1.4B
has answer100.0% true
true 100.0%false 0.0%
is yes no42.6% true
true 42.6%false 57.4%
is open ended57.4% true
true 57.4%false 42.6%
5.0
Flesch–Kincaid grade
US school grade level
4.8
Automated readability index
Frequent terms
dogusesizecatyesworklikefitsmalldonwaterproductdogslargeneedgoodthinkknowtanklongsuredoorcatsinchescagefoodgreatcollarhopewantbigtimeboxhelpsfilterlittleworkscomelitterboughtlbsplasticwaypetmediumbuyinsidedoesnlovefine
Topic clusters

Topic 0

tank
filter
water
gallon
pump
use
fish
need

Topic 1

cat
litter
box
use
love
work
door
kitten

Topic 2

color
ship
amazon
order
item
price
shipping
sorry

Topic 3

cage
hamster
wheel
rabbit
bird
pig
guinea
rat

Topic 4

collar
dog
seat
work
leash
bark
harness
walk

Topic 5

dog
size
pound
large
small
toy
lbs
puppy

Topic 6

inch
dimension
size
wide
height
medium
large
width

Topic 7

blade
clipper
hair
cut
comb
use
dog
coat

Topic 8

ingredient
vitamin
list
acid
product
supplement
calcium
dog

Topic 9

door
flap
window
wall
instal
screen
frame
install
Top hashtags
#1053
#824334
#122
#217
#316
#710
#1285229
#59
#s9
#122888
#308
#1285127
#46
#406
#1284
#85404
#q_2284
#1433
#1533
#1623

Sampled: text metrics from 50K of 73.2K records; topic model from 20K.

Record

Catalog key
amazon_qa_Pet_Supplies
Authors
Wan, Mengting; McAuley, Julian
Year
2016
Source paper
Modeling Ambiguity, Subjectivity, and Diverging Viewpoints in Opinion Question Answering Systems
DOI / arXiv
10.1109/ICDM.2016.0060
License
No licence stated by the authors (citation requested)
Records
36,607
Languages
en
Collected
2013-2015 (2010s)
Region
Global (inferred: the platform is used worldwide)

Provenance

Originally published at
https://cseweb.ucsd.edu/~jmcauley/datasets.html#amazon_qa link checked
Hosted copy
Mirrored on echo.directory on 2026-10-02, 4.0 MB across 1 files. Checksums in MANIFEST.json.

How to cite

BibTeX

@misc{echo2026,
  title  = {ECHO: Exploratory Compendium of Humanity Online},
  author = {Switzer, Braden and Zafarani, Reza},
  year   = {2026},
  url    = {https://echo.directory},
  note   = {Syracuse University}
}

@inproceedings{Wan_2016,
  title     = {Modeling Ambiguity, Subjectivity, and Diverging Viewpoints in Opinion Question Answering Systems},
  url       = {http://dx.doi.org/10.1109/ICDM.2016.0060},
  doi       = {10.1109/icdm.2016.0060},
  booktitle = {2016 IEEE 16th International Conference on Data Mining (ICDM)},
  publisher = {IEEE},
  author    = {Wan, Mengting and McAuley, Julian},
  year      = {2016},
  month     = Dec,
  pages     = {489–498}
}

APA

Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory

Wan, M., & McAuley, J. (2016). Amazon QA — Pet Supplies [Data set]. https://doi.org/10.1109/ICDM.2016.0060

MLA

Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.

Wan, Mengting, and Julian McAuley. Amazon QA — Pet Supplies. 2016, doi.org/10.1109/ICDM.2016.0060.

BibTeX · RIS · CSL-JSON

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