Google Scholar Research Scraper

Extract comprehensive scholarly information from academic databases and research platforms

Automate the collection of academic publications, citation metrics, and research profiles from leading scholarly databases. Perfect for researchers, students, and institutions who need systematic literature reviews without manual data gathering.

Workflow Purpose

Business Objectives

Primary Goal: Automate academic data extraction from scholarly databases to eliminate time-consuming manual literature search

Secondary Benefits:

• Generate datasets for systematic reviews and meta-analyses
• Track research trends and citation patterns
• Support grant applications with literature documentation
• Monitor academic impact and collaboration networks

Expected Results: Obtain complete academic datasets including publications, citations, and bibliometric data for up to 100 records per run

Target Users

Primary User Groups:

• Academic researchers and faculty
• Graduate students and PhD candidates
• Research institutions and libraries
• Academic publishers and journal editors

Technical Requirements: No programming experience needed, basic understanding of academic databases helpful

Use Cases:

• Systematic literature reviews and meta-analyses
• Citation analysis and bibliometric studies
• Research trend identification
• Academic profile building and impact assessment

Usage Guidelines and Scope

Input Parameters

Output Data

Core Data Fields:

• Publication Information: Title, abstract, publication date, journal name
• Author Details: Names, affiliations, institutional addresses
• Citation Metrics: Citation count, h-index, impact factor
• Identifiers: DOI, PubMed ID, arXiv ID, paper URLs
• Classification: Keywords, subject categories, research fields

Export Formats: CSV, JSON, Excel, BibTeX

Supported Scope

Primary Academic Platforms:

• Google Scholar, PubMed, IEEE Xplore, ACM Digital Library
• JSTOR, ResearchGate, Academia.edu, arXiv
• University repositories and institutional databases

Scale Capacity: Designed for medium to large datasets (50-500 publications per execution)

Technical Considerations:

• Some databases require institutional access
• Citation counts may vary between platforms
• Recent publications may have limited metadata

Workflow Construction Details

Parameters and Browser Configuration

Core Parameter Setup:

• target_url: Primary academic database or search platform
• search_keywords: Specific research terms or author names
• data_limit: Collection limit (maximum 500 publications)
• publication_year: Temporal filtering for focused reviews

Browser Settings: Automatically configured with academic-optimized settings for database access

Workflow Process

1. Parameter Setup

Input Parameters:
├── target_url: "https://scholar.google.com/"
├── search_keywords: "machine learning healthcare"
├── data_limit: 100
└── publication_year: "2022-2024"

2. Browser Initialization

• Start: Set up browser with academic-optimized settings
• Configure appropriate user agent for database access

3. Search & Navigation

• Visit Page: Navigate to target academic database
• Input Text: Enter research keywords
• Apply Filters: Set date ranges and document type filters
• Execute Search: Initiate search query

4. Data Collection Loop

• Loop Control: Continue until data_limit reached or results exhausted
• Extract Metadata: Collect publication information:
• • Titles, abstracts, and author details
  • Citation counts and bibliometric data
  • Publication venues and dates
  • DOI and access links
• Handle Pagination: Navigate through result pages
• Error Handling: Retry failed extractions

5. Data Export

• Data Validation: Verify completeness and accuracy
• Format Export: Generate CSV, Excel, JSON, or BibTeX outputs
• Quality Report: Provide summary statistics

Quick Start Guide

5-Minute Setup Experience

1. Create Account: Visit browseract.com to create your account
2. Select Template: Find "Academic Research Data Scraper" in the template library
3. Configure Parameters:

"target_url": "https://scholar.google.com/",
"search_keywords": "artificial intelligence education",
"data_limit": 50,
"publication_year": "2023-2024"

1. Launch Workflow: Click "Start" and monitor progress
2. Download Results: Export data in CSV, Excel, or BibTeX format

Usage Examples

// Systematic review collection
"target_url": "https://pubmed.ncbi.nlm.nih.gov/",
"search_keywords": "COVID-19 machine learning diagnosis",
"data_limit": 200,
"publication_year": "2020-2024"

// Author citation analysis
"target_url": "https://scholar.google.com/",
"search_keywords": "author:\"John Smith\" computer vision",
"data_limit": 100

Typical Application Scenarios

Academic Applications

Literature Reviews: Comprehensive data collection for meta-analyses and systematic reviews

Bibliometric Analysis: Citation pattern analysis and research impact assessment

Grant Writing: Literature documentation for funding applications

Research Monitoring: Track personal citations and identify collaboration opportunities

Technical Integration

API Integration with Make:

Browser Act integrates with Make through our API workflow system, enabling academic research automation without coding.

Common Integration Patterns:

• Reference Management: Auto-import publications into Zotero or Mendeley
• Research Alerts: Weekly notifications for new papers matching criteria
• Impact Monitoring: Monthly citation metrics and research impact reports

For detailed integration steps, visit our API Integration Guide.

Data Compliance and Privacy

Academic Data Ethics

Data Source: Exclusively collects publicly available academic information from legitimate scholarly databases

Best Practices:

• Respect database terms of service and fair use policies
• Maintain appropriate usage rates
• Follow institutional access requirements
• Support proper citation and attribution practices

🚀 Start Using Today!

1. Create Free Account - Quick registration with immediate credits
2. Try Academic Scraper - Experience research automation

💡 Need Custom Academic Workflows?

Contact Options:

• 📧 Email Support: service@browseract.com
• 💬 Discord Community: Join Browser Act Discord

Custom Services:

• Specialized database integration
• Advanced bibliometric analysis workflows
• Multi-language database support

Feedback Channels

• Discord Community: Real-time discussions and support
• Email Feedback: support@browseract.com

Last Updated: September 2025