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--- |
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license: apache-2.0 |
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language: |
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- ind |
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pretty_name: "Twitter Indonesia Sarcastic" |
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--- |
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# Twitter Indonesia Sarcastic |
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Twitter Indonesia Sarcastic is a dataset intended for sarcasm detection in the Indonesian language. This dataset is introduced in [Khotijah et al. (2020)](https://dl.acm.org/doi/10.1145/3406601.3406624), whereby Indonesian tweets are collected and labeled as either sarcastic or non-sarcastic. We took the [raw data](https://github.com/skhotijah/using-lstm-for-context-based-approach-of-sarcasm-detection-in-twitter/blob/main/dataset/Indonesia/imbalanced.csv), and performed several cleaning procedures such as: sentence order re-reversal, 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. |
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## Dataset Structure |
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### Data Instances |
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```py |
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{ |
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'tweet': 'Terima kasih bapak <username> telah mengendalikan banjir dengan baik sehingga Jakarta saat ini tidak ada lagi yang tidak banjir.. Semua sudah merata.. ?????? <hashtag>', |
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'label': 1 |
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} |
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``` |
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### Data Fields |
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- `tweet`: PII-masked Twitter tweet content. |
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- `label`: `0` for non-sarcastic, `1` for sarcastic. |
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### Data Splits |
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| Split | #sarcastic | #non sarcastic | #total | |
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| --------------------------- | :--------: | :------------: | :----: | |
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| `train` | 470 | 1408 | 1878 | |
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| `test` | 134 | 404 | 538 | |
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| `validation` | 67 | 201 | 268 | |
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| Total (cleaned; balanced) | 671 | 2013 | 2684 | |
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| Total (cleaned; unbalanced) | 671 | 12190 | 12861 | |
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| Total (raw) | 4350 | 13368 | 17718 | |
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### Dataset Directory |
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```sh |
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twitter_indonesia_sarcastic |
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├── README.md |
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├── data # re-balanced dataset |
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│ ├── test.csv |
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│ ├── train.csv |
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│ └── validation.csv |
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└── raw_data |
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├── khotijah.csv # raw dataset |
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└── khotijah_cleaned.csv # cleaned dataset |
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``` |
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## Authors |
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Twitter Indonesia Sarcastic is prepared by: |
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<a href="https://github.com/w11wo"> |
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<img src="https://github.com/w11wo.png" alt="GitHub Profile" style="border-radius: 50%;width: 64px;border: solid 1px #fff;margin:0 4px;"> |
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</a> |
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## References |
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```bibtex |
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@inproceedings{10.1145/3406601.3406624, |
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author = {Khotijah, Siti and Tirtawangsa, Jimmy and Suryani, Arie A.}, |
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title = {Using LSTM for Context Based Approach of Sarcasm Detection in Twitter}, |
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year = {2020}, |
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isbn = {9781450377591}, |
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publisher = {Association for Computing Machinery}, |
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address = {New York, NY, USA}, |
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url = {https://doi.org/10.1145/3406601.3406624}, |
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doi = {10.1145/3406601.3406624}, |
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booktitle = {Proceedings of the 11th International Conference on Advances in Information Technology}, |
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articleno = {19}, |
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numpages = {7}, |
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keywords = {context, Sarcasm detection, paragraph2vec, lstm, deep learning}, |
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location = {, Bangkok, Thailand, }, |
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series = {IAIT '20} |
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} |
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@inproceedings{abu-farha-etal-2022-semeval, |
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title = "{S}em{E}val-2022 Task 6: i{S}arcasm{E}val, Intended Sarcasm Detection in {E}nglish and {A}rabic", |
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author = "Abu Farha, Ibrahim and |
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Oprea, Silviu Vlad and |
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Wilson, Steven and |
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Magdy, Walid", |
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editor = "Emerson, Guy and |
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Schluter, Natalie and |
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Stanovsky, Gabriel and |
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Kumar, Ritesh and |
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Palmer, Alexis and |
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Schneider, Nathan and |
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Singh, Siddharth and |
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Ratan, Shyam", |
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booktitle = "Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)", |
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month = jul, |
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year = "2022", |
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address = "Seattle, United States", |
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publisher = "Association for Computational Linguistics", |
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url = "https://aclanthology.org/2022.semeval-1.111", |
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doi = "10.18653/v1/2022.semeval-1.111", |
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pages = "802--814", |
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} |
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``` |
