---
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
dataset_info:
  features:
  - name: gender
    dtype: string
  - name: name_first_word
    dtype: string
  splits:
  - name: train
    num_bytes: 2804876
    num_examples: 166533
  download_size: 793609
  dataset_size: 2804876
license: unknown
task_categories:
- text-classification
language:
- ar
pretty_name: ArabGend
size_categories:
- 100K<n<1M
tags:
- Gender Identification
---
# Dataset Card for "ArabGend: Gender Analysis and Inference on Arabic Twitter"

## Paper:
Hamdy Mubarak, Shammur Absar Chowdhury, and Firoj Alam. 2022. ArabGend: Gender Analysis and Inference on Arabic Twitter. In Proceedings of the Eighth Workshop on Noisy User-generated Text (W-NUT 2022), pages 124–135, Gyeongju, Republic of Korea. Association for Computational Linguistics.