Science Mapping Analysis: A Primer with Biblioshiny. Questo articolo non è disponibile.Science Mapping Analysis: A Primer with Biblioshiny

Every year, millions of scientific articles are published across thousands of journals. How can researchers navigate this ever-expanding ocean of knowledge, identify the most influential works, and uncover the hidden structures that shape a scientific field? Science Mapping Analysis: A Primer with Biblioshiny provides a comprehensive, hands-on guide to bibliometric analysis and science mapping, the quantitative study of scientific literature through citation patterns, keyword co-occurrences, and collaboration networks. Written by two leading experts who created bibliometrix, the most widely adopted open-source tool in the field, this book bridges the gap between methodological rigor and practical accessibility. Organized around the SAAS workflow, the eleven chapters take the reader from foundational concepts to advanced techniques: descriptive profiling of sources, authors, and documents; conceptual structure mapping through thematic analysis; intellectual structure analysis via co-citation and bibliographic coupling; social structure exploration through co-authorship networks; and content analysis of key publications. Every method is explained with its theoretical underpinnings and demonstrated step by step through Biblioshiny, a point-and-click web interface that requires no programming expertise. A common example runs through all chapters, showing how different techniques illuminate different facets of the same field. Mathematical formulations are included where they clarify the logic; worked examples make every analysis immediately reproducible. Whether you are a PhD student mapping your research landscape for the first time, a seasoned scholar conducting a systematic literature review, a research manager assessing the dynamics of a scientific domain, or an instructor teaching quantitative research methods, this book equips you with the conceptual foundations and practical skills to transform raw bibliographic data into meaningful knowledge maps.