Datasets:
Languages:
English
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Language Creators:
found
Annotations Creators:
expert-generated
Source Datasets:
original
Tags:
License:
# 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. | |
"""TODO: Add a description here.""" | |
import csv | |
import datasets | |
_CITATION = """\ | |
@inproceedings{gautam2020metooma, | |
title={# MeTooMA: Multi-Aspect Annotations of Tweets Related to the MeToo Movement}, | |
author={Gautam, Akash and Mathur, Puneet and Gosangi, Rakesh and Mahata, Debanjan and Sawhney, Ramit and Shah, Rajiv Ratn}, | |
booktitle={Proceedings of the International AAAI Conference on Web and Social Media}, | |
volume={14}, | |
pages={209--216}, | |
year={2020} } | |
""" | |
_DESCRIPTION = """\ | |
The dataset consists of tweets belonging to #MeToo movement on Twitter, labelled into different categories. | |
Due to Twitter's development policies, we only provide the tweet ID's and corresponding labels, | |
other data can be fetched via Twitter API. | |
The data has been labelled by experts, with the majority taken into the account for deciding the final label. | |
We provide these labels for each of the tweets. The labels provided for each data point | |
includes -- Relevance, Directed Hate, Generalized Hate, | |
Sarcasm, Allegation, Justification, Refutation, Support, Oppose | |
""" | |
_TRAIN_DOWNLOAD_URL = "https://raw.githubusercontent.com/akash418/public-data-repo/main/MeTooMMD_train.csv" | |
_TEST_DOWNLOAD_URL = "https://raw.githubusercontent.com/akash418/public-data-repo/main/MeTooMMD_test.csv" | |
class Metooma(datasets.GeneratorBasedBuilder): | |
"""Metooma dataset -- Dataset providing labeled information for tweets belonging to the MeToo movement""" | |
VERSION = datasets.Version("1.1.0") | |
def _info(self): | |
# This method pecifies the datasets.DatasetInfo object which contains informations and typings for the dataset | |
return datasets.DatasetInfo( | |
# This is the description that will appear on the datasets page. | |
description=_DESCRIPTION, | |
features=datasets.Features( | |
{ | |
"TweetId": datasets.Value("string"), | |
"Text_Only_Informative": datasets.ClassLabel(names=["Text Non Informative", "Text Informative"]), | |
"Image_Only_Informative": datasets.ClassLabel( | |
names=["Image Non Informative", "Image Informative"] | |
), | |
"Directed_Hate": datasets.ClassLabel(names=["Directed Hate Absent", "Directed Hate Present"]), | |
"Generalized_Hate": datasets.ClassLabel( | |
names=["Generalized Hate Absent", "Generalized Hate Present"] | |
), | |
"Sarcasm": datasets.ClassLabel(names=["Sarcasm Absent", "Sarcasm Present"]), | |
"Allegation": datasets.ClassLabel(names=["Allegation Absent", "Allegation Present"]), | |
"Justification": datasets.ClassLabel(names=["Justification Absent", "Justification Present"]), | |
"Refutation": datasets.ClassLabel(names=["Refutation Absent", "Refutation Present"]), | |
"Support": datasets.ClassLabel(names=["Support Absent", "Support Present"]), | |
"Oppose": datasets.ClassLabel(names=["Oppose Absent", "Oppose Present"]), | |
} | |
), | |
supervised_keys=None, | |
# Homepage of the dataset for documentation | |
homepage="https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/JN4EYU", | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
"""Returns SplitGenerators.""" | |
train_path = dl_manager.download_and_extract(_TRAIN_DOWNLOAD_URL) | |
test_path = dl_manager.download_and_extract(_TEST_DOWNLOAD_URL) | |
return [ | |
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}), | |
datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": test_path}), | |
] | |
def _generate_examples(self, filepath): | |
"""Yields examples.""" | |
with open(filepath, encoding="utf-8") as csv_file: | |
csv_reader = csv.reader( | |
csv_file, | |
quotechar='"', | |
delimiter=",", | |
quoting=csv.QUOTE_ALL, | |
skipinitialspace=True, | |
) | |
for id_, row in enumerate(csv_reader): | |
( | |
tweet_id, | |
text_informative_label, | |
image_informative_label, | |
dir_hate_label, | |
gen_hate_label, | |
sarcasm_label, | |
allegtation_label, | |
justification_label, | |
refutation_label, | |
support_label, | |
oppose_label, | |
) = row | |
yield id_, { | |
"TweetId": tweet_id, | |
"Text_Only_Informative": int(text_informative_label), | |
"Image_Only_Informative": int(image_informative_label), | |
"Directed_Hate": int(dir_hate_label), | |
"Generalized_Hate": int(gen_hate_label), | |
"Sarcasm": int(sarcasm_label), | |
"Allegation": int(allegtation_label), | |
"Justification": int(justification_label), | |
"Refutation": int(refutation_label), | |
"Support": int(support_label), | |
"Oppose": int(oppose_label), | |
} | |