Datasets:
The dataset preview is not available for this split.
Error code: StreamingRowsError
Exception: NonStreamableDatasetError
Message: Streaming is not possible for this dataset because data host server doesn't support HTTP range requests. You can still load this dataset in non-streaming mode by passing `streaming=False` (default)
Traceback: Traceback (most recent call last):
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 495, in xopen
file_obj = fsspec.open(file, mode=mode, *args, **kwargs).open()
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/core.py", line 419, in open
return open_files(
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/core.py", line 272, in open_files
fs, fs_token, paths = get_fs_token_paths(
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/core.py", line 586, in get_fs_token_paths
fs = filesystem(protocol, **inkwargs)
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/registry.py", line 252, in filesystem
return cls(**storage_options)
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/spec.py", line 76, in __call__
obj = super().__call__(*args, **kwargs)
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/implementations/zip.py", line 54, in __init__
self.zip = zipfile.ZipFile(self.fo, mode=mode)
File "/usr/local/lib/python3.9/zipfile.py", line 1266, in __init__
self._RealGetContents()
File "/usr/local/lib/python3.9/zipfile.py", line 1329, in _RealGetContents
endrec = _EndRecData(fp)
File "/usr/local/lib/python3.9/zipfile.py", line 263, in _EndRecData
fpin.seek(0, 2)
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/implementations/http.py", line 737, in seek
raise ValueError("Cannot seek streaming HTTP file")
ValueError: Cannot seek streaming HTTP file
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/workers/datasets_based/src/datasets_based/workers/first_rows.py", line 485, in compute_first_rows_response
rows = get_rows(
File "/src/workers/datasets_based/src/datasets_based/workers/first_rows.py", line 120, in decorator
return func(*args, **kwargs)
File "/src/workers/datasets_based/src/datasets_based/workers/first_rows.py", line 176, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 917, in __iter__
for key, example in ex_iterable:
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 113, in __iter__
yield from self.generate_examples_fn(**self.kwargs)
File "/tmp/modules-cache/datasets_modules/datasets/ar_sarcasm/946b5574cab73f8afb77406014d21a41f3d73d0d1922b8a675fa7449190b9753/ar_sarcasm.py", line 94, in _generate_examples
with open(filepath, encoding="utf-8") as f:
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/streaming.py", line 70, in wrapper
return function(*args, use_auth_token=use_auth_token, **kwargs)
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 498, in xopen
raise NonStreamableDatasetError(
datasets.download.streaming_download_manager.NonStreamableDatasetError: Streaming is not possible for this dataset because data host server doesn't support HTTP range requests. You can still load this dataset in non-streaming mode by passing `streaming=False` (default)Need help to make the dataset viewer work? Open an discussion for direct support.
Dataset Card for ArSarcasm
Dataset Summary
ArSarcasm is a new Arabic sarcasm detection dataset. The dataset was created using previously available Arabic sentiment analysis datasets (SemEval 2017 and ASTD) and adds sarcasm and dialect labels to them.
The dataset contains 10,547 tweets, 1,682 (16%) of which are sarcastic.
For more details, please check the paper From Arabic Sentiment Analysis to Sarcasm Detection: The ArSarcasm Dataset
Supported Tasks and Leaderboards
You can get more information about an Arabic sarcasm tasks and leaderboard here.
Languages
Arabic (multiple dialects)
Dataset Structure
Data Instances
{'dialect': 1, 'original_sentiment': 0, 'sarcasm': 0, 'sentiment': 0, 'source': 'semeval', 'tweet': 'نصيحه ما عمرك اتنزل لعبة سوبر ماريو مش زي ما كنّا متوقعين الله يرحم ايامات السيقا والفاميلي #SuperMarioRun'}
Data Fields
- tweet: the original tweet text
- sarcasm: 0 for non-sarcastic, 1 for sarcastic
- sentiment: 0 for negative, 1 for neutral, 2 for positive
- original_sentiment: 0 for negative, 1 for neutral, 2 for positive
- source: the original source of tweet: SemEval or ASTD
- dialect: 0 for Egypt, 1 for Gulf, 2 for Levant, 3 for Magreb, 4 for Modern Standard Arabic (MSA)
Data Splits
The training set contains 8,437 tweets, while the test set contains 2,110 tweets.
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
Initial Data Collection and Normalization
The dataset was created using previously available Arabic sentiment analysis datasets (SemEval 2017 and ASTD) and adds sarcasm and dialect labels to them.
Who are the source language producers?
SemEval 2017 and ASTD
Annotations
Annotation process
For the annotation process, we used Figure-Eight crowdsourcing platform. Our main objective was to annotate the data for sarcasm detection, but due to the challenges imposed by dialectal variations, we decided to add the annotation for dialects. We also include a new annotation for sentiment labels in order to have a glimpse of the variability and subjectivity between different annotators. Thus, the annotators were asked to provide three labels for each tweet as the following:
- Sarcasm: sarcastic or non-sarcastic.
- Sentiment: positive, negative or neutral.
- Dialect: Egyptian, Gulf, Levantine, Maghrebi or Modern Standard Arabic (MSA).
Who are the annotators?
Figure-Eight crowdsourcing platform
Personal and Sensitive Information
[More Information Needed]
Considerations for Using the Data
Social Impact of Dataset
[More Information Needed]
Discussion of Biases
[More Information Needed]
Other Known Limitations
[More Information Needed]
Additional Information
Dataset Curators
- Ibrahim Abu-Farha
- Walid Magdy
Licensing Information
MIT
Citation Information
@inproceedings{abu-farha-magdy-2020-arabic,
title = "From {A}rabic Sentiment Analysis to Sarcasm Detection: The {A}r{S}arcasm Dataset",
author = "Abu Farha, Ibrahim and Magdy, Walid",
booktitle = "Proceedings of the 4th Workshop on Open-Source Arabic Corpora and Processing Tools, with a Shared Task on Offensive Language Detection",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resource Association",
url = "https://www.aclweb.org/anthology/2020.osact-1.5",
pages = "32--39",
language = "English",
ISBN = "979-10-95546-51-1",
}
Contributions
Thanks to @mapmeld for adding this dataset.
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