metadata

license: apache-2.0
dataset_info:
  features:
    - name: hotel_id
      dtype: int64
    - name: user_id
      dtype: string
    - name: title
      dtype: string
    - name: text
      dtype: string
    - name: overall
      dtype: float64
    - name: cleanliness
      dtype: float64
    - name: value
      dtype: float64
    - name: location
      dtype: float64
    - name: rooms
      dtype: float64
    - name: sleep_quality
      dtype: float64
    - name: stay_year
      dtype: int64
    - name: post_date
      dtype: timestamp[ns]
    - name: freq
      dtype: int64
    - name: review
      dtype: string
    - name: char
      dtype: int64
    - name: lang
      dtype: string
  splits:
    - name: train
      num_bytes: 368237342
      num_examples: 201295
  download_size: 220909380
  dataset_size: 368237342
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
task_categories:
  - text-classification
language:
  - en
pretty_name: sentiment
size_categories:
  - 10K<n<100K

TripAdvisor Easy Dataset

This repository contains a dataset of hotel reviews and ratings collected from TripAdvisor, which has been processed by us. The dataset includes reviews of various hotels along with metadata such as multiple-aspect ratings and review texts. Please refer to our GitHub repohttps://github.com/jniimi/tripadvisor_dataset.

The data is originally distributed by Jiwei Li et al. (2013) and is hosted on his website http://www.cs.cmu.edu/~jiweil/html/hotel-review.html.

Dataset Details

Dataset Description

The contents of the two datasets (.csv and .pkl) are same; however, we recommend using pickle file (.pkl) which retains information on pandas variable types and np.nan for missing values, especially datetime. In the original data, the various variables were stored in JSON format, but we have reorganised them so that the reviews and ratings are combined in one line as a pandas data set.

Since the original dataset has various language, we used machine learning to extract posts where reviews are written in English. Specifically, we adopted `fastText`　(https://fasttext.cc) by Meta, utilizing the pre-trained model `lid.176.bin`.

Language(s) (NLP): English
License: Apache-2.0

Dataset Sources [optional]

Repository: https://nlp.stanford.edu/~bdlijiwei/Code.html
Paper: Li et al. (2023) (Details are shown in Citation section)

Uses

You can load data using datasets package as:

from datasets import load_dataset
df = load_dataset("jniimi/tripadvisor")

Direct Use

This data is suitable for Aspect-based Sentiment Analysis (AbSA), as the same way that TripAdvisor data has already been used in many previous studies.

Out-of-Scope Use

Please follow the policy of the original data source.

Dataset Structure

The dataset includes the following columns in each line:

hotel_id: Unique identifier for hotels.
user_id: Unique identifier for users.
title: Heading of the user review.
text: Actual text of the review.
review: reviews combined as follows: title \n text
overall: The rating given by the user.
cleanliness: The rating regarding the cleanliness.
value: The rating regarding the value.
location: The rating regarding the location.
rooms: The rating regarding the rooms.
sleep_quality: The rating regarding the sleep quality.
date_stayed: The date when the user stayed.
date: The date when the review was posted.

Dataset Creation

Citation

BibTeX:

@misc{tripadvisor_dataset, author = {Junichiro, Niimi}, title = {Hotel Review Dataset (English)}, year = {2024}, howpublished = {\url{https://github.com/jniimi/tripadvisor_dataset}} }

APA:

Original paper:

Li, J., Ott, M., & Cardie, C. (2013, October). Identifying manipulated offerings on review portals. In Proceedings of the 2013 conference on empirical methods in natural language processing (pp. 1933-1942). https://aclanthology.org/D13-1199/

Dataset Card Authors

jniimi (@JvckAndersen)