Abstract:
This study presents an automated methodology to support systematic literature reviews SLRs using open resources specifically Google Scholar as the data source and R as the analytical tool The approach responds to the limitations faced by researchers without access to commercial databases like Scopus or Web of Science The six-stage pipeline includes configuring the R environment extracting and parsing HTML content classifying documents via regular expressions and storing structured data To validate the process 50 documents were extracted using the query psychotherapy AND PTSD with 76 percent identified as theses highlighting the abundance of grey literature in open platforms The automated classification achieved 92 percent agreement with manual review demonstrating reliability The use of R significantly reduces time and human error improving the transparency and reproducibility of SLRs in low-resource settings The study also addresses challenges associated with scraping Google Scholar and outlines future directions including machine learning enhancements and user-friendly interfaces for non-programmers
