Abstract
Systematic literature reviews (SLRs) commonly use keyword co-occurrence analysis for thematic mapping, but standard tools (e.g., VOSviewer, Bibliometrix) are limited to symmetric pairwise relationships. The aim of this study is to formalize author keyword association rule extracting (ARM) as a repeatable, complementary method for thematic mapping in SLR and to evaluate its analytical value relative to standard co-occurrence methods. We apply the Apriori algorithm to author keywords from Scopus and demonstrate it on two datasets: a medium one (597 publications on CSR and consumer behavior) and a large one (14,302 publications on gamification and marketing). Comparing ARM results with VOSviewer co-occurrence maps, we find ARM reveals directional dependencies and multi-item themes that symmetric analyses miss. We propose a three-step framework to incorporate ARM into the PRISMA synthesis stage and discuss using ARM-derived themes for embedding-based screening in EmbedSLR.
Paper Type
Short Paper
DOI
10.62036/ISD.2026.47
Association Rules of Author Keywords for Thematic Mapping in Systematic Literature Reviews
Systematic literature reviews (SLRs) commonly use keyword co-occurrence analysis for thematic mapping, but standard tools (e.g., VOSviewer, Bibliometrix) are limited to symmetric pairwise relationships. The aim of this study is to formalize author keyword association rule extracting (ARM) as a repeatable, complementary method for thematic mapping in SLR and to evaluate its analytical value relative to standard co-occurrence methods. We apply the Apriori algorithm to author keywords from Scopus and demonstrate it on two datasets: a medium one (597 publications on CSR and consumer behavior) and a large one (14,302 publications on gamification and marketing). Comparing ARM results with VOSviewer co-occurrence maps, we find ARM reveals directional dependencies and multi-item themes that symmetric analyses miss. We propose a three-step framework to incorporate ARM into the PRISMA synthesis stage and discuss using ARM-derived themes for embedding-based screening in EmbedSLR.
Recommended Citation
Frankowski, P.K., Wiśniewska, J. & Matysik, S.(2026). Association Rules of Author Keywords for Thematic Mapping in Systematic Literature Reviews. In M. Valenta, B. Mannová, R. Pergl, A. Przybylek, M. Lang, H. Linger, C. Schneider, N. Iivari, & E. Insfran (Eds.), Making ISD Sustainable: Reloaded with AI and Automation (ISD2026 Proceedings). Prague, Czech Republic: Czech Technical University in Prague. ISBN: 978-80-01-07585-2. https://doi.org/10.62036/ISD.2026.47