Published 2013 | Version v3
Open dataset

Multi-aspect Reviews

  • 1. University of California San Diego
  • 2. Stanford University

Description

Description

The Multi-aspect Reviews dataset captures reviews with multiple rated dimensions collected by Julian McAuley's lab (University of California San Diego): beer reviews from Ratebeer and Beeradvocate, including sensory aspects such as taste, look, feel, and smell. It includes anonymized user IDs, beer/brewer IDs, aspect-specific ratings, review text, product category, and ABV, available as two separate datasets — Ratebeer (40,213 users, 110,419 items, 2,855,232 ratings, Apr 2000 – Nov 2011) and BeerAdvocate (33,387 users, 66,051 items, 1,586,259 ratings, Jan 1998 – Nov 2011).

Please cite the following if you use the data:

Learning attitudes and attributes from multi-aspect reviews
Julian McAuley, Jure Leskovec, Dan Jurafsky
ICDM, 2012
DOI: https://dl.acm.org/doi/10.1109/ICDM.2012.110

From amateurs to connoisseurs: modeling the evolution of user expertise through online reviews
Julian McAuley, Jure Leskovec
WWW, 2013
DOI: https://dl.acm.org/doi/10.1145/2488388.2488466

Details

Resource type Open dataset
Title Multi-aspect Reviews
Creators
  • McAuley, Julian1 ORCID icon
  • Leskovec, Jure2 ORCID icon
  • Jurafsky, Dan2 ORCID icon
  • Publisher University of California San Diego
    Year of publication 2013
    Dates of collection April 2000 – November 2011 ; January 1998 – January 2011
    Research fields Economics Psychology Sociology Political Science Economic & Social History Communication Sciences Educational Research Business Administration Other
    Size 1 GB
    Formats JSON format (.json)
    External resource https://cseweb.ucsd.edu/~jmcauley/datasets.html#multi_aspect

    Additional details

    Related works

    Is cited by
    Journal article: 10.1145/3514094.3534128 (DOI)
    Is described by
    Conference paper: 10.1109/ICDM.2012.110 (DOI)
    Conference paper: 10.1145/2488388.2488466 (DOI)