AI Science Scout: Automated Research & Write Article Assistant (semanticscholar.org)

Detail

Are you spending hours manually collecting Semantic Scholar search data—queries, results, paper titles, authors, abstracts, citations, and more? With millions of academic papers, preprints, and scholarly resources to browse through, finding the right data or conducting research has become incredibly time-consuming for researchers, academics, analysts, and scientists.

BrowserAct automates the entire process. Extract structured data from Semantic Scholar in minutes, not hours—no coding required.

What Does BrowserAct Semantic Scholar Scraper Do?

Automatically extract comprehensive Semantic Scholar resource data with our powerful Semantic Scholar scraper tool. Capture paper titles, abstracts, authors, publication years, citation counts, venue details, influence metrics, and links to papers from any Semantic Scholar page. Enjoy flexible filtering and output options for comprehensive market analysis—no coding required.

Our Semantic Scholar scraper is built for seamless integration with automation platforms like Make.com, making it ideal for ongoing monitoring and competitive intelligence tasks.

What Data Can I Extract from Semantic Scholar?

With BrowserAct's Semantic Scholar Scraper, you can pull a wide range of publicly available data for analysis. Here's a breakdown:

Semantic Scholar Search Results & Features

Paper titles
Abstracts and summaries
Authors and affiliations
Publication years and venues
Citation counts
Influence and key paper metrics
PDF and DOI links
Related papers and topics

Key Features of Semantic Scholar Scraper

Customizable Parameters: Adjust extraction scope to match your research needs
Flexible Selection: Set max items for bulk extraction across multiple pages
Comprehensive Data Capture: Extracts complete search profiles with all metadata
Structured Output: Preserves data relationships for easy analysis
Multi-Page Support: Compatible with search results, topic pages, and paper listings
Automation-Ready: Seamlessly integrates with Make.com and other platforms

How to Scrape Semantic Scholar

Quick Start Guide: How to Use Semantic Scholar Scraper in One Click

If you want to quickly start experiencing scraping Semantic Scholar, simply use our pre-built "Semantic Scholar Scraper" template for instant setup and start scraping Semantic Scholar effortlessly.

Register Account: Create a free BrowserAct account using your email
Configure Parameters: Fill in necessary inputs like Target_url (e.g., "https://www.semanticscholar.org/search?q=example") – or use defaults to learn how to scrape Semantic Scholar quickly
Start Execution: Click "Start" to run the workflow
Download Data: Once complete, download the results file from Semantic Scholar scraping

How to Build a Semantic Scholar Scraper Workflow: Step by Step

Semantic Scholar Scraper workflow building with BrowserAct requires no coding skills—it's automation-ready and easy to set up. Follow these step-by-step instructions to get started.

Determine Your Scope

Decide the number of results to extract (e.g., 50 results with complete details). Adjust parameters based on your research needs.

Start Node Parameter Settings

SemanticScholar_Link: Enter your Semantic Scholar link (e.g., https://www.semanticscholar.org/)

Note: Customize based on needs—works with search results, topic pages, or paper listings.

Visit Page

In the prompt box, enter Visit / SemanticScholar_Link – this will navigate to the target URL.

Add Extract Data

In the prompt box, enter:

Extract name/title and add it to "Name" 
- add Authors to "Authors" 
- add Abstract to "Abstract" 
- Add link to the item to "URL"

Note: You can specify the exact location of the data to be collected on the page to increase the accuracy of data extraction.

Output Data

Export in JSON, CSV, XML, or Excel formats.

Key Benefits of Semantic Scholar Scraper

Semantic Scholar Scraper offers a range of advantages that make data extraction simple, efficient, and powerful. Here's why it's a top choice for Semantic Scholar web scraping:

✅ No Coding Required: Set up and run extractions effortlessly without any programming skills—perfect for beginners and pros alike

✅ Customizable and Flexible: Adjust parameters like item limits, data fields, and target URLs to tailor results to your exact needs

✅ Structured Data Output: Maintains organized data in structured formats (e.g., JSON, CSV, Excel) for easy analysis and integration

✅ Automation Integration: Seamlessly works with Make, n8n, and other platforms for scheduled, hands-off web scraping

✅ Cost-Effective: Start with free trials for small-scale tasks, scaling affordably for larger datasets while respecting Semantic Scholar's policies

✅ Accurate and Reliable: Handles automatic page loading, uses 'N/A' for missing data, and includes rate limit handling to ensure consistent results

These benefits make Semantic Scholar Scraper an efficient tool for turning raw Semantic Scholar data into actionable insights.

Who Can Use Semantic Scholar Scraper?

Semantic Scholar Scraper is designed for anyone needing quick, reliable access to Semantic Scholar data. It's ideal for a variety of users, including:

Researchers & Scientists: Discover high-impact papers and track citation trends
Academics & Professors: Analyze author influence and publication networks
Students & PhD Candidates: Conduct literature reviews and identify key references
Digital Libraries & Curators: Manage scholarly content with comprehensive metadata
Market Researchers & Analysts: Extract data for innovation tracking and R&D intelligence
AI & NLP Developers: Gather insights on models, datasets, and evaluation metrics
Small Labs & Startups: Conduct affordable academic research without needing advanced technical skills
Grant Writers & Funders: Research emerging topics and influential works

No matter your background, if you're looking to scrape Semantic Scholar without hassle, this tool is accessible and effective for both individuals and teams.

Use Cases for Semantic Scholar Scraper

Semantic Scholar Scraper is versatile for various real-world applications. Here are some key ways to use it for extracting and analyzing Semantic Scholar data:

📊 Literature Review: Collect data on papers, abstracts, and citations for systematic analysis

🔍 Citation Intelligence: Scrape citation graphs to identify influential works and research gaps

💰 Impact Analysis: Track citation counts and compare influence across authors or fields

⭐ Quality Assessment: Analyze TL;DR summaries and key phrases to identify high-value papers

🔄 Publication Monitoring: Track new submissions and version updates in specific domains

🛠️ Reference Selection: Build comprehensive bibliographies to curate the best sources for your projects

📈 Trend Tracking: Monitor emerging topics and highly cited papers in the Semantic Scholar ecosystem

🎯 Author Research: Identify leading researchers and assess their publication portfolios

Whether for one-off projects or ongoing monitoring, Semantic Scholar Scraper helps transform scholarly data into valuable insights.

Make.com Integration

BrowserAct's Semantic Scholar Scraper is now available as a native app on Make.com—add it to your scenarios without API hassle.

✅ Automation-Ready: Integrate with Make, n8n, or others for scheduled monitoring

✅ Rate Limit Handling: Built-in delays to comply with Semantic Scholar policies

✅ Multi-Topic Tracking: Run instances for different fields, authors, or timeframes

💡 Use Case Tip: Ideal for citation tracking, literature alerts, and research with complete paper metadata

🚀 Quick Start with Make.com: Search for "BrowserAct" in Make.com's app directory and add it directly—no complex setup

Ready to Transform Your Semantic Scholar Data Collection?

Stop wasting hours on manual data collection. Start scraping Semantic Scholar papers, citations, and insights in minutes with BrowserAct's AI-powered automation.

Try BrowserAct Free → https://www.browseract.com/

No credit card required. Get started in under 5 minutes.