The Rise of AfricaNLP: Contributions, Contributors, and Community Impact (2005-2025)

• URL: http://arxiv.org/abs/2509.25477v3
• Date: Thu, 02 Oct 2025 03:08:37 GMT
• Title: The Rise of AfricaNLP: Contributions, Contributors, and Community Impact (2005-2025)
• Authors: Tadesse Destaw Belay, Kedir Yassin Hussen, Sukairaj Hafiz Imam, Ibrahim Said Ahmad, Isa Inuwa-Dutse, Abrham Belete Haile, Grigori Sidorov, Iqra Ameer, Idris Abdulmumin, Tajuddeen Gwadabe, Vukosi Marivate, Seid Muhie Yimam, Shamsuddeen Hassan Muhammad,
• Abstract summary: This study explores the progress of African NLP (AfricaNLP) by asking basic research questions.<n>We quantitatively examine the contributions of AfricaNLP research using 1.9K NLP paper abstracts, 4.9K author contributors, and 7.8K human-annotated contribution sentences.
• Score: 11.546082225991256
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Natural Language Processing (NLP) is undergoing constant transformation, as Large Language Models (LLMs) are driving daily breakthroughs in research and practice. In this regard, tracking the progress of NLP research and automatically analyzing the contributions of research papers provides key insights into the nature of the field and the researchers. This study explores the progress of African NLP (AfricaNLP) by asking (and answering) basic research questions such as: i) How has the nature of NLP evolved over the last two decades?, ii) What are the contributions of AfricaNLP papers?, and iii) Which individuals and organizations (authors, affiliated institutions, and funding bodies) have been involved in the development of AfricaNLP? We quantitatively examine the contributions of AfricaNLP research using 1.9K NLP paper abstracts, 4.9K author contributors, and 7.8K human-annotated contribution sentences (AfricaNLPContributions) along with benchmark results. Our dataset and continuously existing NLP progress tracking website provide a powerful lens for tracing AfricaNLP research trends and hold potential for generating data-driven literature surveys.

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