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README.md

@@ -1,3 +1,104 @@
 ---
 license: apache-2.0
+language: 
+- ind
+pretty_name: "Twitter Indonesia Sarcastic"
 ---
+
+# Twitter Indonesia Sarcastic
+
+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.
+
+## Dataset Structure
+
+### Data Instances
+
+```py
+{
+    'tweet': 'Terima kasih bapak <username> telah mengendalikan banjir dengan baik sehingga Jakarta saat ini tidak ada lagi yang tidak banjir.. Semua sudah merata.. ?????? <hashtag>',
+    'label': 1
+}
+```
+
+### Data Fields
+
+- `tweet`: PII-masked Twitter tweet content.
+- `label`: `0` for non-sarcastic, `1` for sarcastic.
+
+### Data Splits
+
+| Split                       | #sarcastic | #non sarcastic | #total |
+| --------------------------- | :--------: | :------------: | :----: |
+| `train`                     |    470     |      1408      |  1878  |
+| `test`                      |    134     |      404       |  538   |
+| `validation`                |     67     |      201       |  268   |
+| Total (cleaned; balanced)   |    671     |      2013      |  2684  |
+| Total (cleaned; unbalanced) |    671     |     12190      | 12861  |
+| Total (raw)                 |    4350    |     13368      | 17718  |
+
+### Dataset Directory
+
+```sh
+twitter_indonesia_sarcastic
+├── README.md
+├── data    # re-balanced dataset
+│   ├── test.csv
+│   ├── train.csv
+│   └── validation.csv
+└── raw_data
+    ├── khotijah.csv    # raw dataset
+    └── khotijah_cleaned.csv    # cleaned dataset
+```
+
+## Authors
+
+Twitter 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
+@inproceedings{10.1145/3406601.3406624,
+    author = {Khotijah, Siti and Tirtawangsa, Jimmy and Suryani, Arie A.},
+    title = {Using LSTM for Context Based Approach of Sarcasm Detection in Twitter},
+    year = {2020},
+    isbn = {9781450377591},
+    publisher = {Association for Computing Machinery},
+    address = {New York, NY, USA},
+    url = {https://doi.org/10.1145/3406601.3406624},
+    doi = {10.1145/3406601.3406624},
+    booktitle = {Proceedings of the 11th International Conference on Advances in Information Technology},
+    articleno = {19},
+    numpages = {7},
+    keywords = {context, Sarcasm detection, paragraph2vec, lstm, deep learning},
+    location = {, Bangkok, Thailand, },
+    series = {IAIT '20}
+}
+
+@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",
+}
+```

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