| --- |
| annotations_creators: |
| - crowdsourced |
| language_creators: |
| - found |
| language: |
| - apc |
| - ajp |
| license: |
| - other |
| multilinguality: |
| - monolingual |
| size_categories: |
| - 1K<n<10K |
| source_datasets: |
| - original |
| task_categories: |
| - text-classification |
| task_ids: |
| - sentiment-classification |
| - topic-classification |
| paperswithcode_id: arsentd-lev |
| pretty_name: ArSenTD-LEV |
| dataset_info: |
| features: |
| - name: Tweet |
| dtype: string |
| - name: Country |
| dtype: |
| class_label: |
| names: |
| '0': jordan |
| '1': lebanon |
| '2': syria |
| '3': palestine |
| - name: Topic |
| dtype: string |
| - name: Sentiment |
| dtype: |
| class_label: |
| names: |
| '0': negative |
| '1': neutral |
| '2': positive |
| '3': very_negative |
| '4': very_positive |
| - name: Sentiment_Expression |
| dtype: |
| class_label: |
| names: |
| '0': explicit |
| '1': implicit |
| '2': none |
| - name: Sentiment_Target |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 1233980 |
| num_examples: 4000 |
| download_size: 392666 |
| dataset_size: 1233980 |
| --- |
| |
| # Dataset Card for ArSenTD-LEV |
|
|
| ## Table of Contents |
| - [Dataset Description](#dataset-description) |
| - [Dataset Summary](#dataset-summary) |
| - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
| - [Languages](#languages) |
| - [Dataset Structure](#dataset-structure) |
| - [Data Instances](#data-instances) |
| - [Data Fields](#data-fields) |
| - [Data Splits](#data-splits) |
| - [Dataset Creation](#dataset-creation) |
| - [Curation Rationale](#curation-rationale) |
| - [Source Data](#source-data) |
| - [Annotations](#annotations) |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) |
| - [Considerations for Using the Data](#considerations-for-using-the-data) |
| - [Social Impact of Dataset](#social-impact-of-dataset) |
| - [Discussion of Biases](#discussion-of-biases) |
| - [Other Known Limitations](#other-known-limitations) |
| - [Additional Information](#additional-information) |
| - [Dataset Curators](#dataset-curators) |
| - [Licensing Information](#licensing-information) |
| - [Citation Information](#citation-information) |
| - [Contributions](#contributions) |
|
|
| ## Dataset Description |
|
|
| - **Homepage:** [ArSenTD-LEV homepage](http://oma-project.com/) |
| - **Paper:** [ArSentD-LEV: A Multi-Topic Corpus for Target-based Sentiment Analysis in Arabic Levantine Tweets](https://arxiv.org/abs/1906.01830) |
|
|
| ### 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](http://oma-project.com/ArSenL/ArSenTD_Lev_Intro) |
|
|
| ### 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](https://github.com/moussaKam) for adding this dataset. |
