Amazon QA — Office Products

A Amazon dataset of 43,608 QA pairs in Office Products, 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 Office Products. Suitable for question answering, sentiment analysis, product understanding, conversational AI.

#Mcauley amazon#Office product#Product question answering

Download data BibTeX JSONSimilar datasets

Analytics

Content metrics

43,608 records scored · min–maxmean ± 0.675 σ (the interquartile range if the values are roughly normal)mean

unixTimeμ 1.3B ± 253.3M
min 0max 1.4B
has answer100.0% true
true 100.0%false 0.0%
is yes no48.1% true
true 48.1%false 51.9%
is open ended51.9% true
true 51.9%false 48.1%
5.4
Flesch–Kincaid grade
US school grade level
5.3
Automated readability index
Frequent terms
useyesworkprinterphonepaperinkdonneedlikeknowprintinchesfitsizegoodcartridgesureblackwanttimecomechairthinkworksproductcartridgescolordeskpenlongholdhopegreatbuysetheightboxwaymachinehelpsnewfinethanksseatbaseplasticboughtscancomputer
Topic clusters

Topic 0

phone
battery
handset
cord
power
line
headset
jack

Topic 1

label
tape
wall
mount
glue
stick
door
adhesive

Topic 2

ship
year
sorry
shipping
yes
order
calendar
day

Topic 3

desk
shelf
keyboard
drawer
mouse
monitor
inch
laptop

Topic 4

chair
seat
wheel
cart
height
floor
caster
sit

Topic 5

paper
folder
page
size
pocket
binder
sheet
file

Topic 6

printer
print
paper
laser
work
photo
inkjet
computer

Topic 7

pen
refill
ink
nib
fountain
converter
parker
write

Topic 8

calculator
key
button
time
number
press
enter
clock

Topic 9

cartridge
ink
black
printer
print
canon
color
use

Topic 10

inch
dimension
wide
height
width
high
deep
tall

Topic 11

yes
usa
yep
country
wax
candle
georgia
jack
Show all 14 topics

Topic 12

cut
laminate
blade
pouch
cutter
paper
laminating
sheet

Topic 13

pencil
eraser
lead
erase
marker
dry
sharpen
colored
Top hashtags
#230
#1012
#59
#89
#18
#s7
#66
#655326
#1405
#605
#46204
#545324
#784
#b1h4
#xff1f4
#1573
#506123
#573
#613
#655333

Sampled: text metrics from 50K of 87.2K records; topic model from 20K.

Record

Catalog key
amazon_qa_Office_Products
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
43,608
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, 4.3 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 — Office Products [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 — Office Products. 2016, doi.org/10.1109/ICDM.2016.0060.

BibTeX · RIS · CSL-JSON

Similar datasets 10 all with scores →