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.
| Property | Number | Property | Number |
|---|---|---|---|
| Number of reviews | 373,750 | Median reviews per hotel | 150 |
| Number of hotels | 1,858 | Min reviews per hotel | 3 |
| Avg. reviews per hotel | 264 | Number of users | 30,889 |
| Max reviews per hotel | 5,793 | Avg. reviews per user | 15.8 |
| Median reviews per hotel | 150 | Number of tokens | 8,520,886 |
The following figure depicts the reviews distribution in HARD Datasets; balanced (inner) and unbalanced (outer).
You may refer to our paper, cited below, for details on the dataset.
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data/
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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.
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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.
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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>reviewwhere: 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
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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"