Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
sentiment-classification
Languages:
Arabic
Size:
1K<n<10K
Tags:
License:
File size: 3,424 Bytes
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# coding=utf-8
# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
#
# 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.
# Lint as: python3
"""Arabic Jordanian General Tweets."""
from __future__ import absolute_import, division, print_function
import os
import openpyxl # noqa: requires this pandas optional dependency for reading xlsx files
import pandas as pd
import datasets
_DESCRIPTION = """\
Arabic Jordanian General Tweets (AJGT) Corpus consisted of 1,800 tweets \
annotated as positive and negative. Modern Standard Arabic (MSA) or Jordanian dialect.
"""
_CITATION = """\
@inproceedings{alomari2017arabic,
title={Arabic tweets sentimental analysis using machine learning},
author={Alomari, Khaled Mohammad and ElSherif, Hatem M and Shaalan, Khaled},
booktitle={International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems},
pages={602--610},
year={2017},
organization={Springer}
}
"""
_URL = "https://raw.githubusercontent.com/komari6/Arabic-twitter-corpus-AJGT/master/"
class AjgtConfig(datasets.BuilderConfig):
"""BuilderConfig for Ajgt."""
def __init__(self, **kwargs):
"""BuilderConfig for Ajgt.
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(AjgtConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
class AjgtTwitterAr(datasets.GeneratorBasedBuilder):
"""Ajgt dataset."""
BUILDER_CONFIGS = [
AjgtConfig(
name="plain_text",
description="Plain text",
)
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"text": datasets.Value("string"),
"label": datasets.features.ClassLabel(
names=[
"Negative",
"Positive",
]
),
}
),
supervised_keys=None,
homepage="https://github.com/komari6/Arabic-twitter-corpus-AJGT",
citation=_CITATION,
)
def _split_generators(self, dl_manager):
urls_to_download = {
"train": os.path.join(_URL, "AJGT.xlsx"),
}
downloaded_files = dl_manager.download(urls_to_download)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
]
def _generate_examples(self, filepath):
"""Generate examples."""
with open(filepath, "rb") as f:
df = pd.read_excel(f, engine="openpyxl")
for id_, record in df.iterrows():
tweet, sentiment = record["Feed"], record["Sentiment"]
yield str(id_), {"text": tweet, "label": sentiment}
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