Audience Engagement with Arabic Women's Social Empowerment and Wellbeing: A Decadal Corpus

2026-05-21 · Source: Computation and Language · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Data Science & Analytics, Social Sciences & Behavioral Studies · Depth: Intermediate, quick

Summary

The Arabic Women and Society Corpus is a ten-year collection of 252,487 public Arabic Facebook posts focused on women's empowerment and social wellbeing. Collected from 51,660 pages across 77 countries between 2013 and 2024, this corpus captures over 267 million user interactions, including shares, comments, and emotional reactions. The data underwent an automated processing pipeline involving language identification, normalization, and metadata cleaning to ensure reliability. This unique dataset offers a view into audience sentiment and social attention, enabling large-scale analysis of gender discourse, social reform, and emotional engagement across various Arabic dialects. It supports research in Arabic natural language processing, computational social science, and digital communication studies, with the dataset available upon request for research purposes.

Key takeaway

For research scientists exploring social dynamics or language processing in the Arabic-speaking world, you should consider requesting access to the Arabic Women and Society Corpus. This dataset offers a unique, decadal view of audience engagement with women's empowerment and wellbeing topics, providing rich data for computational social science and natural language processing studies. Its comprehensive collection of posts and interaction metrics from 77 countries enables robust analysis of evolving gender discourse and social attention.

Key insights

The corpus provides a decadal view of Arabic women's social empowerment discourse on Facebook.

Principles

• Large-scale social media data reveals evolving discourse.
• Engagement metrics quantify audience sentiment.
• Automated data processing ensures corpus reliability.

Method

An automated pipeline performed language identification, normalization, and metadata cleaning on Facebook posts from 2013-2024, collecting engagement metrics.

In practice

• Analyze gender discourse evolution over a decade.
• Study social reform movements in Arabic contexts.
• Research emotional engagement across Arabic dialects.

Topics

• Arabic NLP
• Computational Social Science
• Gender Discourse
• Social Media Data
• Women's Empowerment
• Corpus Development

Best for: NLP Engineer, AI Scientist, Research Scientist, Data Scientist

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Editorial summary, takeaway, and curation by AIssential. Original article published by Computation and Language.