README.md

---
license: cc-by-4.0
configs:
  - config_name: Sampled data
    data_files:
      - split: train
        path: MMT_LID_sample10.csv
  - config_name: Distributed data
    data_files:
      - split: train
        path: MMT_distributable_without_tweets.csv
task_categories:
- text-classification
language:
- hi
- en
- gu
- bn
- ta
tags:
- code-mixing
- Twitter-data
size_categories:
- 1M<n<10M
---

# MMT (Multilingual and Multi‑Topic Twitter Language Identification Dataset)

**MMT: A Multilingual and Multi‑Topic Indian Social Media Dataset** is a large-scale language identification dataset derived from 1.7 million tweets collected from Indian Twitter/X, annotated with coarse and fine-grained language labels. It supports research on multilingual and code-mixed text in noisy, real-world social media settings.

## 📁 Files Included in This Release

### `MMT_LID_sample10.csv`: A small illustrative sample of **10 tweets**, allowed under Twitter/X’s non-automated sharing exemption.

**Columns:**
- `tweets`: Raw tweet text  
- `language_detected`: Predicted language (automated)  
- `is_the_language_correct`: Binary correctness flag (1 = correct)  
- `correct_language_tag`: Human-corrected language tag

> ⚠️ Not for bulk distribution. For research use only.

### `MMT_distributable_without_tweets.csv`: This is the main distributable dataset (≈1.35M tweets), compliant with Twitter Developer Policy.

**Includes:**
- Tweet IDs  
- Derived metadata (e.g., language tags, annotations, splits)  
- No tweet text, media, or JSON content

### 📥 Request Full Dataset Access

👉 **[Request Full Dataset Access via Google Form](https://forms.gle/eigzBQttprATLqcSA)**  
**Please fill this form to request access to the full version of the MMT LID Full Dataset.** </br> 
**Mail at: [lingo@iitgn.ac.in](lingo@iitgn.ac.in)**


### `twitter_dataset_release_rules.txt`: Compliance documentation outlining redistribution rules from Twitter/X's developer policy and privacy guidelines (GDPR/CCPA).


### Dataset Usage Disclaimer ‼️

<span style="color:red">
This dataset is derived from public social media content and may contain:
<ul>
  <li>Offensive, sensitive, or biased material</li>
  <li>Non-standard or noisy language</li>
</ul>
Please use it responsibly and in accordance with ethical guidelines and applicable data protection laws (GDPR, CPRA).
</span>

**Note**: “This release contains only Post IDs/User IDs and our derived labels/metadata. We do not distribute tweet text, media, or full tweet/user JSON. Requesters must hydrate IDs via the X API and must honor deletions, privatizations, and other changes; any valid takedown request will be processed within 24 hours. Distribution is subject to the X Developer Policy, including the 1,500,000-IDs limit, and to applicable privacy laws (e.g., GDPR/CPRA). As a result, we have a reduced version of the file: MMT_distributable_without_tweets, which is under 1.5M posts (i.e., in the ballpark of 1.35M).”


## ⚖️ Licensing & Attribution

- **Curated by:** [Lingo Research Group at IIT Gandhinagar](https://lingo.iitgn.ac.in/)
- **Languages**: Multilingual (Hindi, English, Gujarati, Bengali, Tamil, etc.)  
- **License**: cc-by-4.0 (for derived annotations only)  
- **Tweet Content License**: Subject to [Twitter Developer Policy](https://developer.x.com/en/developer-terms/policy)

## 📚 Citation

If you use this dataset in your research, please cite the following:
```
@inproceedings{dalal-etal-2023-mmt,
    title = "{MMT}: A Multilingual and Multi-Topic {I}ndian Social Media Dataset",
    author = "Dalal, Dwip  and
      Srivastava, Vivek  and
      Singh, Mayank",
    booktitle = "Proceedings of the First Workshop on Cross-Cultural Considerations in NLP (C3NLP)",
    month = may,
    year = "2023",
    address = "Dubrovnik, Croatia",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.c3nlp-1.6/",
    doi = "10.18653/v1/2023.c3nlp-1.6",
    pages = "47--52"
}
```