README.md

---
license: cc-by-nc-sa-4.0
task_categories:
- text-classification
language:
- bn
pretty_name: Ben-Sarc
size_categories:
- 10K<n<100K
tags:
- sarcasm
- bengali sarcasm
- bengali sarcasm detection
source_datasets:
- original
---
# Dataset Card for 'Ben-Sarc'

<!-- Provide a quick summary of the dataset. -->

This repository contains the dataset of the paper titled [**"Ben-Sarc: A Self-Annotated Corpus for Sarcasm Detection from Bengali Social Media Comments and Its Baseline Evaluation"**](https://doi.org/10.1017/nlp.2024.11) published in [***Natural Language Processing**(formerly known as Natural Language Engineering)*](https://www.cambridge.org/core/journals/natural-language-engineering) journal by [*Cambridge University Press*](https://www.cambridge.org/).

## Dataset Details

### Dataset Description

<!-- Provide a longer summary of what this dataset is. -->


We are releasing a large-scale self-annotated Bengali corpus for sarcasm detection research problem in the Bengali language named `Ben-Sarc` containing 25,636 comments, manually collected from different public Facebook pages and evaluated by external evaluators. 


### Dataset Sources 

<!-- Provide the basic links for the dataset. -->

- **Repository:** [https://github.com/sanzanalora/Ben-Sarc](https://github.com/sanzanalora/Ben-Sarc)
- **Paper:** [Ben-Sarc: A Self-Annotated Corpus for Sarcasm Detection from Bengali Social Media Comments and Its Baseline Evaluation](https://engrxiv.org/index.php/engrxiv/preprint/view/2102)
<!-- - **Demo [optional]:** [More Information Needed]

## Uses -->

<!-- Address questions around how the dataset is intended to be used. -->

### Direct Use

<!-- This section describes suitable use cases for the dataset. -->

The `Ben-Sarc` corpus can be used any kind of used for low-resource NLP applications.

<!-- ### Out-of-Scope Use -->

<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->

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## Dataset Structure
### Data Instances
The `Ben-Sarc` dataset is in `.xlsx` format. One example from the `Ben-Sarc` dataset is given below:
```
|----|------------------------------------------------------------------------------------------------------------|----------|
| id |                                           Text                                                             | Polarity |
|----|------------------------------------------------------------------------------------------------------------|----------|
| 589|তোমারে ভাবিয়া সারারাত জাগিয়া ঘুম মোর হয়েছে নষ্ট বুকের বামপাশে চিনচিন ব্যাথা করে একি গ্যাস্ট্রিক না প্রেম হচ্ছে না স্পষ্ট ।          |    1     |
|----|------------------------------------------------------------------------------------------------------------|----------|
```


### Data Fields

<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->

-  `id`: A string representing the text ID.
-  `Text` : A string containing the text.
-  `Polarity` : A number containing the polarity of the text

`Polarity` of the `Ben-Sarc` is defined as follows:
```
            `0` indicates Non-Sarcastic Text
            
            `1` indicates Sarcastic Text
```


## Dataset Creation

### Curation Rationale

<!-- Motivation for the creation of this dataset. -->

[Detailed in the paper](https://engrxiv.org/index.php/engrxiv/preprint/view/2102)

### Source Data

<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
[Detailed in the paper](https://engrxiv.org/index.php/engrxiv/preprint/view/2102)

#### Data Collection and Processing

<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->

[Detailed in the paper](https://engrxiv.org/index.php/engrxiv/preprint/view/2102)

#### Who are the source data producers?

<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->

[Detailed in the paper](https://engrxiv.org/index.php/engrxiv/preprint/view/2102)

### Annotations 

<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
[Detailed in the paper](https://engrxiv.org/index.php/engrxiv/preprint/view/2102)

#### Annotation process

<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->

[Detailed in the paper](https://engrxiv.org/index.php/engrxiv/preprint/view/2102)

#### Who are the annotators?

<!-- This section describes the people or systems who created the annotations. -->

[Detailed in the paper](https://engrxiv.org/index.php/engrxiv/preprint/view/2102)

<!--#### Personal and Sensitive Information -->

<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->

<!--[More Information Needed]

## Bias, Risks, and Limitations-->

<!-- This section is meant to convey both technical and sociotechnical limitations. -->

<!--[More Information Needed]

### Recommendations-->

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. 

Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.-->

## Additional Information

- **Funded by:** [Non-Funded Research]
- **Language(s) (NLP):** [Bengali]
- **License:** Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)](https://creativecommons.org/licenses/by-nc-sa/4.0/). 
## Citation 

<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->

If you use our dataset, please cite the following paper:
```
@article{Lora_Shahariar_Nazmin_Rahman_Rahman_Bhuiyan_Shah_2024,
  title={Ben-Sarc: A self-annotated corpus for sarcasm detection from Bengali social media comments and its baseline evaluation},
  DOI={10.1017/nlp.2024.11},
  journal={Natural Language Processing},
  author={Lora, Sanzana Karim and Shahariar, G. M. and Nazmin, Tamanna and Rahman, Noor Nafeur and Rahman, Rafsan and Bhuiyan, Miyad and Shah, Faisal Muhammad},
  year={2024},
  pages={1–26}} 

```



<!--## Glossary [optional]-->

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## Dataset Card Authors [optional]

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## Dataset Card Contact

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