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license: cc-by-4.0
task_categories:
- text-classification
- text-retrieval
- translation
language:
- zh
- en
size_categories:
- 1K<n<10K
---
## Dataset
We introduce CodedLang, a dataset of 7,744 Chinese Google Maps reviews, including 900 reviews with span-level annotations of coded language.
### Taxonomy
We define 7 categories of coded language:
- **Ambiguous Homophones**
- **Non-Lexical Homophones**
- **Phonetic Substitution**
- **Emoji Substitution**
- **Orthographic Substitution**
- **Cross-Lingual Phonetic Encoding**
- **Cipher**
### Data Sources
Our dataset is constructed based on two large-scale Google Maps review datasets:
- [Google Local Reviews (Li et al., 2022, Yan et al., 2023)](https://cseweb.ucsd.edu/~jmcauley/datasets.html#google_local ): 666 million reviews
- [Google Restaurant Reviews (Yan et al., 2023)](https://cseweb.ucsd.edu/~jmcauley/datasets.html#google_restaurants ): 1.77 million reviews
### Annotations
Each sample includes:
- `id`: Index of the review
- `original_review`: Original Chinese review text
- `translated_review`: English translation of the original review
- Note: 309 reviews are missing translations from the raw Google Reviews dataset and are kept as-is
- `rating`: Review rating (1–5 stars)
- `char_mask_review`: Character-level masked version of the review
- `span_mask_review`: Span-level masked version of the review
- `decode_review`: Decoded version of the review, where coded language is replaced with the intended meaning.
- `coded_lang_class`: Taxonomy label(s) for coded language classes
- `code_span`: Text span of coded expressions
- `coded_language`: Binary label
- `1`: contains coded language
- `0`: non-coded review
---
## Citation
If you find this work useful for your research, please cite our paper:
```
@inproceedings{wan2026newspaper,
title={"Newspaper Eat" Means "Not Tasty": A Taxonomy and Benchmark for Coded Languages in Real-World Chinese Online Reviews},
author={Wan, Ruyuan and Li, Changye and Huang, Ting-Hao'Kenneth'},
booktitle={The 64th Annual Meeting of the Association for Computational Linguistics},
year={2026}
}
```
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