Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
sentiment-classification
Languages:
Arabic
Size:
1K - 10K
License:
File size: 3,177 Bytes
b8efa50 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 |
# coding=utf-8
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Dataset of 8364 restaurant reviews scrapped from qaym.com in Arabic for sentiment analysis"""
from __future__ import absolute_import, division, print_function
import csv
import datasets
_CITATION = """\
@InProceedings{10.1007/978-3-319-18117-2_2,
author="ElSahar, Hady
and El-Beltagy, Samhaa R.",
editor="Gelbukh, Alexander",
title="Building Large Arabic Multi-domain Resources for Sentiment Analysis",
booktitle="Computational Linguistics and Intelligent Text Processing",
year="2015",
publisher="Springer International Publishing",
address="Cham",
pages="23--34",
isbn="978-3-319-18117-2"
}
"""
_DESCRIPTION = """\
Dataset of 8364 restaurant reviews scrapped from qaym.com in Arabic for sentiment analysis
"""
_HOMEPAGE = "https://github.com/hadyelsahar/large-arabic-sentiment-analysis-resouces"
_DOWNLOAD_URL = (
"https://raw.githubusercontent.com/hadyelsahar/large-arabic-sentiment-analysis-resouces/master/datasets/RES1.csv"
)
class ArResReviews(datasets.GeneratorBasedBuilder):
"""Dataset of 8364 restaurant reviews in Arabic for sentiment analysis"""
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"polarity": datasets.ClassLabel(names=["negative", "positive"]),
"text": datasets.Value("string"),
"restaurant_id": datasets.Value("string"),
"user_id": datasets.Value("string"),
}
),
homepage=_HOMEPAGE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
data_dir = dl_manager.download_and_extract(_DOWNLOAD_URL)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_dir}),
]
def _generate_examples(self, filepath):
"""Generate arabic restaurant reviews examples."""
with open(filepath, encoding="utf-8") as csv_file:
next(csv_file)
csv_reader = csv.reader(
csv_file, quotechar='"', delimiter=",", quoting=csv.QUOTE_ALL, skipinitialspace=True
)
for id_, row in enumerate(csv_reader):
polarity, text, restaurant_id, user_id = row
polarity = "negative" if polarity == "-1" else "positive"
yield id_, {"polarity": polarity, "text": text, "restaurant_id": restaurant_id, "user_id": user_id}
|