elnagara/HARD-Arabic-Dataset

Hotels Arabic-Reviews Dataset

34

13 commits

updated Dec 18, 2018

See the code

README

HARD: Hotel Arabic-Reviews Dataset

Description

This dataset contains 93700 hotel reviews in Arabic language. The hotel reviews were collected from Booking.com website during June/July 2016. The reviews are expressed in Modern Standard Arabic as well as dialectal Arabic. The following table summarize some tatistics on the HARD Dataset.

PropertyNumberPropertyNumber
Number of reviews373,750Median reviews per hotel150
Number of hotels1,858Min reviews per hotel3
Avg. reviews per hotel264Number of users30,889
Max reviews per hotel5,793Avg. reviews per user15.8
Median reviews per hotel150Number of tokens8,520,886

The following figure depicts the reviews distribution in HARD Datasets; balanced (inner) and unbalanced (outer).

alt text

You may refer to our paper, cited below, for details on the dataset.

Dataset

  • data/

    • balanced-reviews.tsv: a tab separated file containing a balanced dataset of positive and negative reviews. The ratings are mapped into positive (ratings 4 & 5) and negative (ratings 1 & 2). No nuetral reviews are included. The dataset consists of 93700 reviews; 46850 for each positive and negative classes.

    • balanced-reviews.csv: same as above dataset but using the CSV format. The format of each review record is:

                  rating<TAB>sentiment<TAB>review_id<TAB>hotel_id<TAB>user_id<TAB>no_nights<TAB>review
      
    • unbalanced-reviews.tsv.rar: the whole dataset of 373,750 reviews. This is a clean dataset that includes all reviews.

    • unbalanced-reviews.csv.rar: same as above dataset but using the CSV format. The format of each review record is:

                   rating<TAB>review_id<TAB>hotel_id<TAB>user_id<TAB>no_nights<TAB>review
                   
      

      where: rating: the user rating on a scale of 1 to 5 sentiment: -1 (negative) and 1 (positive) For the balanced dataset review id: the id of the review (to access the review of a specific review) hotel id: the id of the hotel user id: the type of user (single, couple, ...) nights: number of nights stayed in the hotel review: the text of the review

Citation

Please cite the following paper if you decise to use the dataset:

Elnagar A., Khalifa Y.S., Einea A. (2018) Hotel Arabic-Reviews Dataset Construction for Sentiment Analysis Applications. 
In: Shaalan K., Hassanien A., Tolba F. (eds) Intelligent Natural Language Processing: Trends and Applications. 
Studies in Computational Intelligence, vol 740, pp: 35-52. Springer International Publishing. 
doi="10.1007/978-3-319-67056-0_3. url="https://doi.org/10.1007/978-3-319-67056-0_3"

elnagara/HARD-Arabic-Dataset

Hotels Arabic-Reviews Dataset

34

13 commits

updated Dec 18, 2018

See the code

README

HARD: Hotel Arabic-Reviews Dataset

Description

This dataset contains 93700 hotel reviews in Arabic language. The hotel reviews were collected from Booking.com website during June/July 2016. The reviews are expressed in Modern Standard Arabic as well as dialectal Arabic. The following table summarize some tatistics on the HARD Dataset.

PropertyNumberPropertyNumber
Number of reviews373,750Median reviews per hotel150
Number of hotels1,858Min reviews per hotel3
Avg. reviews per hotel264Number of users30,889
Max reviews per hotel5,793Avg. reviews per user15.8
Median reviews per hotel150Number of tokens8,520,886

The following figure depicts the reviews distribution in HARD Datasets; balanced (inner) and unbalanced (outer).

alt text

You may refer to our paper, cited below, for details on the dataset.

Dataset

  • data/

    • balanced-reviews.tsv: a tab separated file containing a balanced dataset of positive and negative reviews. The ratings are mapped into positive (ratings 4 & 5) and negative (ratings 1 & 2). No nuetral reviews are included. The dataset consists of 93700 reviews; 46850 for each positive and negative classes.

    • balanced-reviews.csv: same as above dataset but using the CSV format. The format of each review record is:

                  rating<TAB>sentiment<TAB>review_id<TAB>hotel_id<TAB>user_id<TAB>no_nights<TAB>review
      
    • unbalanced-reviews.tsv.rar: the whole dataset of 373,750 reviews. This is a clean dataset that includes all reviews.

    • unbalanced-reviews.csv.rar: same as above dataset but using the CSV format. The format of each review record is:

                   rating<TAB>review_id<TAB>hotel_id<TAB>user_id<TAB>no_nights<TAB>review
                   
      

      where: rating: the user rating on a scale of 1 to 5 sentiment: -1 (negative) and 1 (positive) For the balanced dataset review id: the id of the review (to access the review of a specific review) hotel id: the id of the hotel user id: the type of user (single, couple, ...) nights: number of nights stayed in the hotel review: the text of the review

Citation

Please cite the following paper if you decise to use the dataset:

Elnagar A., Khalifa Y.S., Einea A. (2018) Hotel Arabic-Reviews Dataset Construction for Sentiment Analysis Applications. 
In: Shaalan K., Hassanien A., Tolba F. (eds) Intelligent Natural Language Processing: Trends and Applications. 
Studies in Computational Intelligence, vol 740, pp: 35-52. Springer International Publishing. 
doi="10.1007/978-3-319-67056-0_3. url="https://doi.org/10.1007/978-3-319-67056-0_3"