An Analysis of the news coverage of Fintech in Africa: a natural language processing approach

Hamid Nach ()
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Hamid Nach: UQAR

Quality & Quantity: International Journal of Methodology, 2025, vol. 59, issue 2, No 6, 839-877

Abstract: Abstract This study analyzes a corpus of 2,409 English-language news articles published between 2013 and 2023, focusing on the Fintech sector in Africa, using Natural Language Processing (NLP) techniques. The research aims to uncover the dominant themes, narratives, and trends in media coverage of African Fintech, enriching the understanding of how the sector is represented. The analysis reveals a significant increase in Fintech-related news coverage over the decade, with a marked rise post-2020, reflecting a burgeoning industry. Text mining methods, including word cloud visualization, geographical mention analysis, sentiment analysis, and topic modelling, are applied to extract insights from the data. The study contributes to the understanding of media’s role in shaping perceptions of the African Fintech sector and provides valuable insights for stakeholders in policymaking, investment, and technology development.

Keywords: Africa; Fintech; NLP; Media; Text mining; News; Content analysis; Sentiment analysis; Topic modelling (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11135-024-02045-y

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