Aggregate research papers, citations, and scholarly content for literature reviews.
Build comprehensive research databases by extracting papers, metadata, and citations from academic repositories.
Academic research requires surveying vast literature: papers, citations, author networks, and research trends. Manual searches across arXiv, PubMed, Google Scholar, and institutional repositories is time-consuming. Automated academic scraping enables researchers to build comprehensive literature databases, track citation networks, and identify emerging research areas systematically.
Research intelligence pipelines combine multiple sources. Repository scrapers extract papers, abstracts, and metadata. Citation parsers build academic graphs showing influence and collaboration patterns. Keyword extractors identify research topics and methodological trends. Together, these feed literature review tools, research recommendation engines, and scientometric analyses.
Respect publisher rights and platform policies. Many academic publishers restrict bulk downloading even for subscribed content. Open access repositories like arXiv explicitly allow scraping. Google Scholar limits automated queries. Consider official APIs when available, respect rate limits, and focus on metadata extraction rather than full-text when licenses are unclear.
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