Abstract
Dark web forums are critical platforms for illicit activities and anonymous communication, making their analysis essential for cybersecurity, law enforcement, and academic research. This systematic literature review synthesises methodologies for data collection and analysis of dark web forum content. Following PRISMA 2020 guidelines, we searched SciSpace, Google Scholar, and PubMed, identifying 364 papers, of which 11 provided detailed methodological insights. Key methodologies include web crawling, machine learning, natural language processing, and social network analysis. Results show the dominance of Python-based automated tools, with hybrid approaches combining automation and manual verification proving most effective. Challenges include ethical considerations, data accessibility, and platform dynamism. The field is maturing but requires standardised frameworks and improved reproducibility. This review outlines current practices, evaluates methodological effectiveness, and suggests future directions for research and application. Keywords: dark web; forums; data collection; analysis methodologies; systematic review; cybersecurity
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