What problem does it solve? Quantitatively mapping a research field's structure, evolution, and key actors is difficult to do rigorously — naive exports and uncleaned data produce meaningless network pictures instead of defensible findings. ## Core Features & Use Cases - Science Mapping: Guides co-citation, bibliographic coupling, co-word, and co-authorship network analysis with VOSviewer, CiteSpace, and Bibliometrix/biblioshiny. - Performance Analysis: Covers productivity and impact metrics including h/g-index, Bradford's law, Lotka's law, and field-normalized citation indicators. - Data Cleaning & Reporting Standards: Enforces thesaurus-based keyword merging, author disambiguation, explicit thresholds, and reproducible reporting per Donthu et al. (2021). - Use Case: An AEC researcher writing a review paper on digital twins in construction exports Scopus records, cleans keywords in VOSviewer, identifies intellectual foundations via co-citation clusters, and reports an emerging research gap. ## Quick Start Help me design a bibliometric analysis of BIM adoption research using my Scopus export, including tool choice, cleaning steps, and cluster interpretation.
