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Sankore

Named after the University of Sankore in Timbuktu — one of the world’s oldest centres of learning. Every figure here is computed from work-level records in our own graph, never copied from a source’s summary count.

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Coverage is partial and says so. A country appears with its research output only once its works have been swept; until then the portal shows whatever the graph happens to hold for it and labels it as exactly that.

Unveiling Sentiments: A Deep Dive Into Sentiment Analysis for Low-Resource Languages—A Case Study on Hausa Texts

2024IEEE AccessJournalOpen access

10.1109/access.2024.3427416 Full text7 citations

Authors

7 authors across 8 institutions in 6 countries.

Harisu Abdullahi ShehuFirst author
Kaloma Usman Majikumna
- University of Maiduguri (NG)
Aminu Bashir Suleiman
- Federal Medical Centre (NG)
- Federal University Dutsin-Ma (NG)
Stephen Luka
- Federal Medical Centre (NG)
- Federal University Dutsin-Ma (NG)
Md. Haidar Sharif
Rabie A. Ramadan
- Cairo University (EG)
Huseyin KusetogullariSenior author

Fields

Assignment is probabilistic — a work belongs to several fields in proportions.

Sentiment Analysis and Opinion Mininglevel 3 · 1.00
Topic Modelinglevel 3 · 1.00
Natural Language Processing Techniqueslevel 3 · 1.00

Sources

Several sources describing one work is the point — it means the record rests on more than one authority.

openalexseen September 9, 2026
2024 · IEEE Access · 7 citations
https://openalex.org/W4400579165

Unveiling Sentiments: A Deep Dive Into Sentiment Analysis for Low-Resource Languages—A Case Study on Hausa Texts · Sankore