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README.md

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----
-license: cc-by-nc-sa-4.0
-dataset_info:
-  features:
-  - name: id
-    dtype: string
-  - name: text
-    dtype: string
-  - name: image
-    dtype: image
-  - name: img_path
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 288846844.171
-    num_examples: 4007
-  - name: dev
-    num_bytes: 45903775.0
-    num_examples: 584
-  - name: test
-    num_bytes: 81778364.176
-    num_examples: 1134
-  download_size: 423373959
-  dataset_size: 416528983.347
----
+# ArMeme Dataset
+
+## Overview
+
+ArMeme is the first multimodal Arabic memes dataset that includes both text and images, collected from various social media platforms. It serves as the first resource dedicated to Arabic multimodal research. While the dataset has been annotated to identify propaganda in memes, it is versatile and can be utilized for a wide range of other research purposes, including sentiment analysis, hate speech detection, cultural studies, meme generation, and cross-lingual transfer learning. The dataset opens new avenues for exploring the intersection of language, culture, and visual communication.
+
+## Dataset Structure
+
+The dataset is divided into three splits:
+- **Train**: The training set
+- **Dev**: The development/validation set
+- **Test**: The test set
+
+Each entry in the dataset includes:
+- `id`: id corresponds to the entry
+- `text`: The textual content associated with the image.
+- `image`: The corresponding image.
+- `img_path`: The file path to the image.
+
+
+## How to Use
+
+You can load the dataset using the `datasets` library from Hugging Face:
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("QCRI/ArMeme")
+```
+
+**Language:** Arabic
+**Modality:** Multimodal (text + image)
+**Number of Samples:** ~6000
+
+
+## License
+
+This dataset is licensed under the **CC-By-NC-SA-4.0** license.
+
+## Citation
+
+```
+@article{alam2024armeme,
+  title={{ArMeme}: Propagandistic Content in Arabic Memes},
+  author={Alam, Firoj and Hasnat, Abul and Ahmed, Fatema and Hasan, Md Arid and Hasanain, Maram},
+  year={2024},
+  journal={arXiv: 2406.03916},
+}
+```
+