📚 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.

🕒 Last updated: 2026-04-16 · 📊 36 fields · 🔄 Runs on Apify cloud or locally · 📁 Export: JSON, CSV, Excel

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

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📋 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.

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🎬 Full Demo

🚧 Coming soon...

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⚙️ Input

Field	Type	Required	Description
maxItems	integer	No	Maximum articles to collect. Free users: limited to 10. Paid users: up to 1,000,000.
startUrl	string	No	Direct PLOS search URL. Mutually exclusive with search filters below.
searchQuery	string	No	Search term (e.g., "genetics", "immunotherapy"). Only works with search filters.
subjectArea	string	No	Filter by subject (150+ options including Biology, Medicine, Neuroscience, Psychology).
author	string	No	Filter by author name to find papers by specific researchers.
publicationDateFrom	string	No	Start date in YYYY-MM-DD format.
publicationDateTo	string	No	End date in YYYY-MM-DD format.

Example 1: Search by topic and subject area

{
  "searchQuery": "genetics",
  "subjectArea": "Genetics",
  "maxItems": 25,
  "publicationDateFrom": "2023-01-01",
  "publicationDateTo": "2024-12-31"
}

Example 2: Find articles by a specific author

{
  "searchQuery": "immunotherapy",
  "author": "Wei Zhang",
  "maxItems": 50
}

⚠️ 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.

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📊 Output

🧾 Schema

Emoji	Field	Type	Description
📝	title	string	Article title
📖	abstract	string	Full article abstract
🔗	doi	string	Digital Object Identifier
🌐	url	string	Article URL
👥	authors	array	List of author objects with names and affiliations
📅	publicationDate	string	Date published
📅	receivedDate	string	Date manuscript was received
📅	acceptedDate	string	Date manuscript was accepted
📂	subjectAreas	array	Research subject categories
🔑	keywords	array	Article keywords
📊	viewCount	number	Total article views
📊	citationCount	number	Total citations received
💾	saveCount	number	Times saved by users
📰	journal	string	Journal name (PLOS ONE, PLOS Biology, etc.)
⚖️	copyright	string	Copyright information
💰	funding	string	Funding statement
📋	competingInterests	string	Competing interests declaration
📄	articleType	string	Research article, review, etc.
🏷️	peerReviewStatus	string	Peer review status
👤	correspondingAuthor	string	Primary contact author
🔗	pdfUrl	string	PDF download link
📎	supportingInformation	array	Links to supporting materials
📊	altmetricScore	number	Altmetric attention score
🔢	volume	string	Journal volume number
🔢	issue	string	Journal issue number
📄	pages	string	Page range
🏫	editorName	string	Handling editor name
🏫	editorAffiliation	string	Editor affiliation
⚖️	license	string	License type
📅	correctionDate	string	Correction date if applicable
🔗	relatedArticles	array	Related article links
🖼️	figureUrls	array	Article figure image URLs
📊	dataAvailability	string	Data availability statement
📅	scrapedAt	string	Data collection timestamp
🔄	retracted	boolean	Whether article was retracted
❌	error	string	Error message if extraction failed

📦 Sample records

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✨ Why choose this Actor

Feature	Details
📊 36 data fields	Titles, authors, abstracts, metrics, funding, review status, and more
🔬 150+ subject areas	Filter by Biology, Medicine, Neuroscience, Psychology, and many more
📅 Date range filtering	Target specific publication windows
👤 Author search	Find all papers by a specific researcher
📊 Impact metrics	View counts, citation counts, and save metrics
📁 Multiple export formats	JSON, CSV, Excel for any workflow
🔄 Automatic pagination	Handles multi-page results without manual intervention

📈 Typical performance: Collects 200+ articles per minute. A dataset of 5,000 articles takes roughly 25 minutes.

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📈 How it compares to alternatives

Feature	This Actor	Manual PLOS Search	Generic Scrapers
36 structured fields per article	✅	❌	Partial
150+ subject area filters	✅	✅ (manual)	❌
Impact metrics (views, citations)	✅	✅ (one at a time)	❌
Author and date filtering	✅	✅ (manual)	Partial
Export to CSV/JSON/Excel	✅	❌	Partial
Scales to 100K+ articles	✅	❌	❌
Scheduled runs	✅	❌	Partial

Purpose-built for PLOS journals, with every metadata field mapped and 150+ subject area filters supported.

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🚀 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.

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💼 Business use cases

Academic Research Build systematic review datasets Track citation networks across PLOS journals Monitor publication trends by subject area Identify high-impact articles in your field	Pharmaceutical & Biotech Monitor drug-related research publications Track clinical study findings Identify potential research collaborators Build literature databases for regulatory submissions
Library & Information Science Analyze journal publishing patterns Track open access adoption metrics Build recommendation systems for researchers Monitor editorial timelines and review processes	Data Science & AI Create biomedical text corpora for NLP Build knowledge graphs from article metadata Train topic classification models Analyze authorship and collaboration patterns

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🔌 Automating PLOS Journals Scraper

Node.js

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });
const run = await client.actor("parseforge/plos-journals-scraper").call({
  searchQuery: "genetics",
  subjectArea: "Genetics",
  maxItems: 100
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python

from apify_client import ApifyClient
client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("parseforge/plos-journals-scraper").call(run_input={
    "searchQuery": "genetics",
    "subjectArea": "Genetics",
    "maxItems": 100
})
items = list(client.dataset(run["defaultDatasetId"]).iterate_items())
print(items)

• 📖 Apify API Reference
• 🐍 Python API Client docs
• 🟢 Node.js API Client docs

Schedules: Set up weekly or monthly runs with Apify Schedules to automatically track new publications in your research area and build historical datasets.

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❓ Frequently Asked Questions

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🔌 Integrate with any app

• 🔗 Make (Integromat) - Connect PLOS article data to 1,000+ apps with visual workflows
• 🔗 Zapier - Trigger actions when new articles matching your criteria are published
• 🔗 Slack - Get notifications in Slack when new PLOS articles appear in your field
• 🔗 Airbyte - Sync article metadata to your data warehouse
• 🔗 GitHub - Automate literature monitoring pipelines with GitHub Actions
• 🔗 Google Drive - Export article data directly to Google Sheets

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🔗 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.

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🆘 Need Help? Open our contact form and we will get back to you within 24 hours. For bug reports, feature requests, or integration help, we are here to assist.

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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.