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Results for "Computational Social Science"

Building Arabic NLP from the Ground Up: Twenty Years of Lessons, Failures, and Open Problems

arXiv ·

This paper reflects on two decades of building NLP resources and research infrastructure for Arabic, an historically underserved language. The first decade focused on foundational linguistic infrastructure, while the second shifted towards computational social science and socially oriented applications. The authors highlight three lessons: dataset building is a social process, communities often matter more than shared tasks, and computational social science exposes challenges beyond traditional NLP training. Why it matters: The paper argues that the most difficult problems in developing NLP for underserved communities are social, institutional, and epistemic, offering critical insights for future research directions in Arabic AI.

JobArabi: An Arabic Corpus and Analysis of Job Announcements from Social Media

arXiv ·

Researchers have introduced JobArabi, a new large-scale corpus consisting of 20,528 Arabic job announcements collected from X between January 2024 and October 2025. The dataset was compiled using a linguistically informed query framework covering various Arabic recruitment expressions, offering metadata like timestamps and geolocation for detailed analysis. Quantitative analysis of JobArabi reveals sociolinguistic patterns, including persistent gendered hiring language, regional occupational demand variations, and emotional framing in recruitment messages. Why it matters: This corpus provides a valuable resource for research in Arabic NLP, computational social science, and digital labor studies, offering unique insights into labor market communication and linguistic change in the Arab world.

Natural language processing is at the top of MBZUAI’s agenda

MBZUAI ·

MBZUAI is prioritizing natural language processing (NLP) research, aiming to be a top university in the field within 12-18 months according to Professor Timothy Baldwin. MBZUAI's NLP department is focusing on deep learning, algorithmic fairness, computational social science and social media analytics. A key area is Arabic NLP, addressing the challenges of dialectal variations and code-switching in social media. Why it matters: This focus on Arabic NLP and real-world problem-solving will contribute to the UAE's ambitious agenda of growing a local AI industry and integrating AI into various sectors.