Data
oclar

oclar

active ARFF Publicly available Visibility: public Uploaded 28-05-2021 by Meilina Reksoprodjo
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Author: Marwan Al Omari, Moustafa Al-Hajj, Nacereddine Hammami, Amani Sabra Source: [UCI](https://archive.ics.uci.edu/ml/datasets/Opinion+Corpus+for+Lebanese+Arabic+Reviews+%28OCLAR%29) - 2019 Please cite: [Paper](https://ieeexplore.ieee.org/document/8716394) Opinion Corpus for Lebanese Arabic Reviews (OCLAR) Data Set The researchers of OCLAR Marwan et al. (2019), they gathered Arabic costumer reviews from and Zomato website on wide scope of domain, including restaurants, hotels, hospitals, local shops, etc. The corpus finally contains 3916 reviews in 5-rating scale. For this research purpose, the positive class considers rating stars from 5 to 3 of 3465 reviews, and the negative class is represented from values of 1 and 2 of about 451 texts. ### Attribute Information: 1. 3916 text reviews 2. 5-rating scale: 1: 303 2. 148 3. 418 4. 734 5. 2313 Positive class includes rating stars from 5 to 3 of 3465 total. Negative class include rating stars from 1 to 2 of 451 total.

3 features

pagenamestring405 unique values
0 missing
reviewstring3096 unique values
0 missing
ratingnumeric5 unique values
0 missing

19 properties

3916
Number of instances (rows) of the dataset.
3
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
1
Number of numeric attributes.
0
Number of nominal attributes.
0
Number of attributes divided by the number of instances.
33.33
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
Average class difference between consecutive instances.
0
Percentage of missing values.

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