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Data · dataset · 2026

Authorship, Collaboration, and Theory Use in African Library and Information Science Journals Indexed in Web of Science:

Listed in Teesside University Research Data Repository

This dataset supports a study examining the use of theory, authorship patterns, and collaboration structures in African Library and Information Science (LIS) journals indexed in Web of Science.

Description

The dataset includes bibliometric and full‑text–derived variables for all research articles published between **2011 and 2020** in the three African LIS journals indexed in Web of Science: - African Journal of Library, Archives and Information Science (AJLAIS) - South African Journal of Libraries and Information Science (SAJLIS) - South African Journal of Information Management (SAJIM) ### Data Contents The dataset contains: - Bibliographic metadata extracted from Web of Science, including article titles, authors, affiliations, publication years, document types, keywords, and citation counts. - Authorship and collaboration indicators, such as number of authors, institutional collaboration, and international collaboration patterns. - Theory‑use variables, derived from full‑text analysis, capturing: - Whether a theory or conceptual framework was used - The type of theory - The depth of theoretical engagement (e.g., superficial mention vs. substantive integration into design, analysis, or interpretation) - Frequency of theoretical references - Citation impact measures, enabling comparison between theoretical and non‑theoretical articles.

Methodological

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Notes

Bibliometric data were retrieved directly from Web of Science. Full‑text articles were manually reviewed to identify theoretical frameworks and assess the depth of theoretical engagement. Coding procedures captured both the presence of theory and the qualitative nature of its application.

Purpose and Significance This dataset enables analysis of how African LIS scholarship engages with theory, how authors collaborate, and how theoretical grounding relates to citation performance. It is the first dataset to focus exclusively on African‑based LIS journals indexed in Web of Science, addressing a gap in prior research that relied on datasets dominated by non‑African journals and authors. Potential Uses Researchers can use this dataset to: - Study theory use in African scholarly communication - Examine collaboration patterns in LIS research - Explore relationships between theoretical grounding and citation impact - Conduct comparative analyses with global LIS literature

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Provenance · 1 source records, 7 field assertions
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