📚 PLOS Journals Scraper

🚀 Extract scholarly article data from PLOS journals in minutes. Filter by search query, subject area, author, or date range. No coding, no subscriptions required.

The PLOS Journals Scraper collects detailed metadata from PLOS ONE and other PLOS journals, the world's largest multidisciplinary open-access publishing platform. Each article record includes 36 structured fields covering titles, abstracts, full author lists, DOIs, impact metrics, peer review status, publication timelines, and funding information. Whether you need 10 articles for a quick literature check or 50,000+ records for a systematic review, this tool handles it automatically.

Built for researchers conducting literature reviews, academics monitoring research trends, science librarians building citation databases, and data teams creating training datasets. The scraper supports keyword search, subject area filtering, author-specific queries, and date range selection. It extracts complete metadata from each article listing, handles pagination, and delivers analysis-ready data in JSON, CSV, or Excel format.

Target Audience	Use Cases
Academic Researchers	Systematic reviews, citation analysis
Science Librarians	Collection building, usage reporting
Pharmaceutical Companies	Drug research monitoring
Data Scientists	NLP corpus creation, metadata analysis
Funding Agencies	Research output assessment
Science Journalists	Trend discovery, story research

📋 What the PLOS Journals Scraper does

• 📝 Extracts article titles and abstracts for literature review, keyword analysis, and topic classification
• 👥 Collects complete author information including names, affiliations, and contribution details for collaboration mapping
• 🔗 Captures DOIs and permanent article links for citation management and direct access to publications
• 📅 Tracks publication timelines with received, accepted, and publication dates for editorial process analysis
• 📊 Gathers impact metrics including view counts, citation counts, and save metrics for measuring article reach
• 📖 Pulls full metadata with subject areas, keywords, funding information, copyright details, and supporting materials

The scraper processes PLOS search results page by page, extracting every available metadata field from each article. Subject area filtering covers 150+ research categories from Biology and Medicine to Neuroscience and Psychology. Date range filtering lets you target specific publication windows.

💡 Why it matters: PLOS ONE alone publishes over 100,000 articles per year. Manually searching, reviewing, and organizing this volume of research is impractical. This scraper delivers clean, structured metadata for any filtered subset in minutes.

📊 Data fields

Each record includes: abstract, acceptedDate, acknowledgments, articleType, authorContributions, authors, authorsInformation, citationsCount, competingInterests, copyrightInformation, dataAvailability, detailUrl, doi, editorInformation, figures, fundingInformation, imageUrl, journal, keywords, openAccessStatus, pdfUrl, peerReviewStatus, publicationDate, receivedDate, references, savesCount, scrapedTimestamp, sections, sharesCount, subjectAreas, supportingInformation, tables, title, viewsCount. All 34 field names come from a real production run, so what you see here is what lands in your dataset.

⚠️ Good to Know: Use either startUrl or the search filters (searchQuery, subjectArea, author, dates), not both. The subject area list includes 150+ options. Free users are automatically limited to 10 items per run.

🚀 How to use

1. Create a free Apify account - Sign up here (includes free credits)
2. Open the PLOS Journals Scraper - Navigate to the Actor page and click "Start"
3. Set your search criteria - Enter a keyword, select a subject area, or filter by author and date range
4. Choose your limit - Set maxItems (free users: up to 10)
5. Run and download - Click "Start", wait for completion, then export as JSON, CSV, or Excel

⏱️ First results appear in under 20 seconds. A typical run of 100 articles completes in about 1 minute.

🔗 Recommended Actors

Actor	Description
📚 PubMed Citation Scraper	Extract citation data and metadata from PubMed biomedical literature
🔬 OpenAlex Scraper	Query 250M+ scholarly records from the OpenAlex open catalog
📰 medRxiv Scraper	Collect health sciences preprint data from medRxiv
🧬 bioRxiv Scraper	Scrape biology preprint articles from bioRxiv
📖 Crossref Scraper	Collect DOI metadata and citation information from Crossref

💡 Pro Tip: Combine the PLOS Journals Scraper with the PubMed Citation Scraper to build a multi-source literature database covering both open access and indexed biomedical research.

Disclaimer: This Actor is provided as-is, without warranty. It is not affiliated with or endorsed by PLOS (Public Library of Science). Use it responsibly and in compliance with applicable terms of service. The authors are not responsible for how the collected data is used. Always verify data accuracy for critical applications.

🆘 Need Help?

If you hit a bug, have questions about setup, or need a scraper we haven't built yet, open our contact form or write to parseforge@protonmail.com. We also take on paid custom data projects.

For faster answers, join our Discord. It's the best place to get support and suggest new actors.