Fine-Grained Propaganda Detection for Hausa: Systematic Review of Resources, Methods, and Future Directions

The proliferation of propaganda through digital platforms threatens information integrity globally. Computational tools for fine-grained persuasion technique detection remain concentrated on English and a few high-resource European languages. Hausa, a Chadic language spoken by over 120 million people across West and Central Africa, lacks systems capable of identifying specific persuasion strategies like loaded language or appeal to authority. This systematic review, conducted following PRISMA 2020 guidelines, synthesises research at the intersection of fine-grained propaganda detection, parameter-efficient transfer learning, cross-lingual knowledge transfer, and African natural language processing (NLP). Thirty-seven studies (2019-2026) were retrieved from IEEE Xplore, ScienceDirect, Scopus, Web of Science, and the ACL Anthology based on strict inclusion criteria. The evidence reveals three primary patterns: (a) fine-grained propaganda detection features mature taxonomies and transformer-based methods, but its empirical base excludes African languages; (b) parameter-efficient methods like Low-Rank Adaptation LoRA match full fine-tuning performance but remain unevaluated for span-level technique detection; and (c) Hausa NLP has largely advanced through binary and coarse classification, leaving a critical gap in fine-grained analysis. A coverage analysis confirms that no existing study addresses fine-grained propaganda detection for Hausa. This review consolidates the evidence in nine tables and seven figures, maps the resource landscape, profiles adaptation trade-offs, and proposes a five-year research roadmap. The roadmap prioritises adapter benchmarking and corpus development (2026-2028), cross-lingual transfer with cultural adaptation (2027-2029), and deployable, resource-efficient systems for African fact-checking organizations (2029-2031). The findings demonstrate that while the technical building blocks for fine-grained propaganda detection in Hausa exist, the intersection remains completely unexplored, presenting a significant opportunity for future research.

Keywords: Fine-grained propaganda detection; cross-lingual transfer learning; parameter-efficient fine-tuning; Hausa; low-resource languages; African language NLP; systematic literature review.