Error code:   ConfigNamesError
Exception:    RuntimeError
Message:      Dataset scripts are no longer supported, but found arsentd_lev.py
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
                  config_names = get_dataset_config_names(
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                                   ^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1031, in dataset_module_factory
                  raise e1 from None
                File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 989, in dataset_module_factory
                  raise RuntimeError(f"Dataset scripts are no longer supported, but found {filename}")
              RuntimeError: Dataset scripts are no longer supported, but found arsentd_lev.py

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Dataset Card for ArSenTD-LEV

Dataset Summary

The Arabic Sentiment Twitter Dataset for Levantine dialect (ArSenTD-LEV) contains 4,000 tweets written in Arabic and equally retrieved from Jordan, Lebanon, Palestine and Syria.

Supported Tasks and Leaderboards

Sentriment analysis

Languages

Arabic Levantine Dualect

Dataset Structure

Data Instances

{'Country': 0, 'Sentiment': 3, 'Sentiment_Expression': 0, 'Sentiment_Target': 'هاي سوالف عصابات ارهابية', 'Topic': 'politics', 'Tweet': 'ثلاث تفجيرات في #كركوك الحصيلة قتيل و 16 جريح بدأت اكلاوات كركوك كانت امان قبل دخول القوات العراقية ، هاي سوالف عصابات ارهابية'}

Data Fields

Tweet: the text content of the tweet
Country: the country from which the tweet was collected ('jordan', 'lebanon', 'syria', 'palestine')
Topic: the topic being discussed in the tweet (personal, politics, religion, sports, entertainment and others)
Sentiment: the overall sentiment expressed in the tweet (very_negative, negative, neutral, positive and very_positive)
Sentiment_Expression: the way how the sentiment was expressed: explicit, implicit, or none (the latter when sentiment is neutral)
Sentiment_Target: the segment from the tweet to which sentiment is expressed. If sentiment is neutral, this field takes the 'none' value.

Data Splits

No standard splits are provided

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

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

[More Information Needed]

Licensing Information

Make sure to read and agree to the license

Citation Information

@article{baly2019arsentd,
  title={Arsentd-lev: A multi-topic corpus for target-based sentiment analysis in arabic levantine tweets},
  author={Baly, Ramy and Khaddaj, Alaa and Hajj, Hazem and El-Hajj, Wassim and Shaban, Khaled Bashir},
  journal={arXiv preprint arXiv:1906.01830},
  year={2019}
}

Contributions

Thanks to @moussaKam for adding this dataset.

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Homepage:

ArSenTD-LEV homepage

Paper:

ArSentD-LEV: A Multi-Topic Corpus for Target-based Sentiment Analysis in Arabic Levantine Tweets