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---
license: apache-2.0
language:
- ind
pretty_name: "Reddit Indonesia Sarcastic"
---
# Reddit Indonesia Sarcastic
Reddit Indonesia Sarcastic is a dataset intended for sarcasm detection in the Indonesian language. This dataset is inspired by the data collection procedure introduced in [Ranti, K.S., & Girsang, A.S (2020)](http://www.warse.org/IJETER/static/pdf/file/ijeter10892020.pdf), whereby Reddit comments from r/indonesia subreddit are collected and filtered by the existence of an `/s` tag at the end of the comment. We collected Reddit comments from 2020-01 to 2023-09 from [Academic Torrents](https://academictorrents.com/details/89d24ff9d5fbc1efcdaf9d7689d72b7548f699fc) and applied the aforementioned procedure. Further, we performed deduplication with minHash LSH, PII masking to remove usernames, hashtags, emails, URLs, and finally a random sampling to limit the non-sarcastic comments. Following [SemEval-2022 Task 6: iSarcasmEval](https://aclanthology.org/2022.semeval-1.111/), we used a 1:3 ratio to balance sarcastic with non-sarcastic comments.
## Dataset Structure
### Data Instances
```py
{
"author": "curuya",
"created_utc": 1584876528,
"score": 7,
"permalink": "/r/indonesia/comments/fmxhfe/jangan_takut_sama_corona_takut_sama_allah/fl6n993/",
"subreddit": "indonesia",
"body": 'taat perintah tuhan : "kalau ada razia mendingan kabur" /s',
"lang_fastText": "id",
"label": 1,
"text": 'taat perintah tuhan : "kalau ada razia mendingan kabur"',
}
```
### Data Fields
- `author`: Comment author.
- `created_utc`: Comment creation time, in UTC.
- `score`: Comment's Reddit voting score.
- `permalink`: Permalink to the Reddit comment.
- `subreddit`: Subreddit name.
- `body`: Raw Reddit comment content.
- `lang_fastText`: Language detected by [fasttext-langdetect](https://github.com/zafercavdar/fasttext-langdetect).
- `label`: `0` for non-sarcastic, `1` for sarcastic.
- `text`: Sarcastic tag-removed, PII-masked version of `body`.
### Data Splits
| Split | #sarcastic | #non sarcastic | #total |
| ------------------ | :--------: | :------------: | :-----: |
| `train` | 2470 | 7411 | 9881 |
| `test` | 706 | 2118 | 2824 |
| `validation` | 353 | 1058 | 1411 |
| Total (balanced) | 3529 | 10587 | 14116 |
| Total (unbalanced) | 3529 | 2616335 | 2619864 |
### Dataset Directory
```sh
reddit_indonesia_sarcastic/
├── README.md
├── data # re-balanced dataset
│ ├── test.json
│ ├── train.json
│ └── validation.json
└── raw_data # raw unbalanced dataset
└── reddit_indonesia_sarcastic.json
```
## Authors
Reddit Indonesia Sarcastic is prepared by:
<a href="https://github.com/w11wo">
<img src="https://github.com/w11wo.png" alt="GitHub Profile" style="border-radius: 50%;width: 64px;border: solid 1px #fff;margin:0 4px;">
</a>
## References
```bibtex
@article{Ranti2020IndonesianSD,
title={Indonesian Sarcasm Detection Using Convolutional Neural Network},
author={Kiefer Stefano Ranti and Abba Suganda Girsang},
journal={International Journal of Emerging Trends in Engineering Research},
year={2020},
url={https://doi.org/10.30534/ijeter/2020/10892020}
}
@article{academicReddit,
title= {Reddit comments/submissions 2005-06 to 2023-09},
journal= {},
author= {stuck_in_the_matrix, Watchful1, RaiderBDev},
year= {},
url= {},
abstract= {Reddit comments and submissions from 2005-06 to 2023-09 collected by pushshift and u/RaiderBDev. These are zstandard compressed ndjson files. Example python scripts for parsing the data can be found here https://github.com/Watchful1/PushshiftDumps},
keywords= {reddit},
terms= {},
license= {},
superseded= {}
}
@inproceedings{abu-farha-etal-2022-semeval,
title = "{S}em{E}val-2022 Task 6: i{S}arcasm{E}val, Intended Sarcasm Detection in {E}nglish and {A}rabic",
author = "Abu Farha, Ibrahim and
Oprea, Silviu Vlad and
Wilson, Steven and
Magdy, Walid",
editor = "Emerson, Guy and
Schluter, Natalie and
Stanovsky, Gabriel and
Kumar, Ritesh and
Palmer, Alexis and
Schneider, Nathan and
Singh, Siddharth and
Ratan, Shyam",
booktitle = "Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)",
month = jul,
year = "2022",
address = "Seattle, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.semeval-1.111",
doi = "10.18653/v1/2022.semeval-1.111",
pages = "802--814",
}
``` |