Amazon QA — Health & Personal Care

A Amazon dataset of 80,496 QA pairs in Health & Personal Care, 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 Health & Personal Care. Suitable for question answering, sentiment analysis, product understanding, conversational AI.

#Mcauley amazon#Personal care#Product question answering

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Analytics

Content metrics

80,496 records scored · min–maxmean ± 0.675 σ (the interquartile range if the values are roughly normal)mean

unixTimeμ 1.3B ± 263.3M
min 0max 1.4B
has answer100.0% true
true 100.0%false 0.0%
is yes no41.5% true
true 41.5%false 58.5%
is open ended58.5% true
true 58.5%false 41.5%
5.6
Flesch–Kincaid grade
US school grade level
5.6
Automated readability index
Frequent terms
useproductyessizelikedonworkknowgoodneedlongwaterfittimehopesurebottlethinkhelpsdateingredientsfreesayssmallhelpgreatexpirationwantworksdaybuycomelargebestinchesbetterboughtyearsoilwayamazonfindorderweightbatterydoesnboxlabeldifferentcontain
Topic clusters

Topic 0

blade
hair
shaver
razor
shave
smell
trimmer
clipper

Topic 1

ship
order
shipping
amazon
price
sorry
know
item

Topic 2

floor
clean
use
stain
tile
wash
work
remove

Topic 3

date
expiration
expire
year
month
bottle
buy
time

Topic 4

seat
chair
toilet
wheel
fit
walker
tub
leg

Topic 5

battery
charge
charger
plug
work
power
voltage
adapter

Topic 6

magnesium
ingredient
vitamin
acid
calcium
list
contain
gelatin

Topic 7

pill
capsule
bottle
swallow
powder
large
tablet
size

Topic 8

inch
scale
weigh
pound
wide
weight
measure
width

Topic 9

size
shoe
knee
wear
large
medium
heel
brace

Topic 10

cuff
strap
arm
wrist
monitor
velcro
small
heart

Topic 11

taste
protein
flavor
mix
carb
like
whey
stevia
Show all 16 topics

Topic 12

heat
microwave
pad
heating
light
hot
bulb
minute

Topic 13

yes
sure
yep
usa
crush
dose
nos
sir

Topic 14

soy
gluten
gmo
free
yeast
non
contain
product

Topic 15

brush
tooth
oral
head
fit
toothbrush
whiten
braun
Top hashtags
#125
#224
#xff1f17
#315
#6425712
#xff0c9
#1280777
#1285156
#652926
#125
#1285
#405
#642585
#96795
#s5
#104
#1285224
#54
#97344
#00003

Sampled: text metrics from 50K of 161K records; topic model from 20K.

Record

Catalog key
amazon_qa_Health_and_Personal_Care
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
80,496
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, 8.1 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 — Health & Personal Care [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 — Health & Personal Care. 2016, doi.org/10.1109/ICDM.2016.0060.

BibTeX · RIS · CSL-JSON

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