| # HinglishMemeX |
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| *A Code-Mixed Multimodal Dataset for Misinformation and Satire Detection in Indian Memes* |
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| ## Overview |
| HinglishMemeX is a curated multimodal dataset consisting of **1,370 Indian social-media memes** that combine **images + Hinglish (Hindi+English code-mixed) text**. Each meme is paired with: |
| - OCR‑extracted Hinglish text |
| - A distilled **English factual claim** |
| - A **supporting evidence URL** (from a trusted fact-checking source) |
| - A **veracity label**: `real`, `fake`, `satire`, or `partially_true` |
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| This dataset is designed for **misinformation detection**, **satire identification**, **multimodal classification**, and **retrieval‑augmented fact verification**. |
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| ## Dataset Structure |
| ``` |
| HinglishMemeX/ |
| ├── images/ |
| │ ├── 000001.jpg |
| │ ├── 000002.jpg |
| │ └── ... |
| ├── metadata.csv |
| ├── README.md |
| ``` |
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| ### Each metadata entry contains: |
| - `id`: unique ID for the meme |
| - `image`: path or URL to the meme image |
| - `ocr_text_hinglish`: OCR text extracted from the meme (Hinglish) |
| - `claim_en`: distilled factual English claim |
| - `evidence_url`: link to fact-checking source |
| - `label`: one of `real`, `fake`, `satire`, `partially_true` |
| - `source`: origin (AltNews, Factly, BOOMLive, satire pages, etc.) |
| - `split`: train / validation / test |
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| ## Tasks Supported |
| - **Multimodal misinformation detection** (4-way classification) |
| - **Satire detection** |
| - **Claim verification** via external evidence |
| - **OCR-based text understanding in code-mixed Hinglish** |
| - **Retrieval-Augmented Generation (RAG)** over evidence URLs |
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| ## Dataset Statistics |
| - **Total memes:** 1,370 |
| - **Classes:** Real, Fake, Satire, Partially True |
| - **Splits:** |
| - Train: ~70% |
| - Validation: ~10% |
| - Test: ~20% |
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| ## Data Collection & Curation |
| - Images collected from **public fact-checking portals** (AltNews, BOOMLive, Factly) and **popular social media satire pages**. |
| - Hinglish text was extracted using **EasyOCR** and **Google Vision API**, followed by light manual correction. |
| - Claims were distilled into short English factual statements. |
| - Evidence URLs were added for transparency and retrieval. |
| - Double annotator labeling with adjudication for disagreements. |
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| ## Benchmarks & Baselines |
| Baseline experiments were conducted using: |
| - **CLIP ViT-L/14** (vision-only) |
| - **CLIP + IndicBERT** (late fusion) |
| - **Cross-attention dual encoders** (deep fusion) |
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| Evaluation metrics: **macro-F1**, **accuracy**, **per-class F1**. |
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| Satire and partially-true memes are particularly challenging due to semantic overlap. |
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| ## Ethical Considerations |
| - Contains politically sensitive content; models trained on this dataset may inherit biases. |
| - Some memes may include misinformation or sensitive themes—handle responsibly. |
| - Recommended to use the dataset for **research only**. |
| - Provide confidence scores and retrieved evidence when deploying models. |
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| ## ⚠️ Limitations |
| - Focused on Indian context → may not generalize globally. |
| - Natural OCR errors remain in some samples. |
| - Subjective boundaries between satire and partially-true content. |
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| ## Loading the Dataset (Hugging Face) |
| ```python |
| from datasets import load_dataset |
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| dataset = load_dataset("pushkarsharma/HinglishMemeX") |
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| def add_path(example): |
| example["image"] = f"images/{example['id']}.jpg" |
| return example |
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| dataset = dataset.map(add_path) |
| ``` |
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| ## License |
| Please refer to the **LICENSE** file for dataset licensing details. |
| Choose a license such as **CC BY 4.0** or **CC BY-SA 4.0** depending on your redistribution permissions. |
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| ## Citation |
| If you use HinglishMemeX, please cite: |
| ``` |
| @misc{hinglishmemex2025, |
| title = {HinglishMemeX: A Code-Mixed Multimodal Dataset for Misinformation and Satire Detection in Indian Memes}, |
| author = {Sharma, Pushkar}, |
| year = {2025}, |
| institution = {Indian Institute of Technology Patna} |
| } |
| ``` |
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| ## Contact |
| **Maintainer:** Pushkar Sharma |
| Email: *pushkarrokhel@gmail.com* |
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| Thank you for using HinglishMemeX! |
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| license: apache-2.0 |
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