Brief

This Browseract workflow is designed to streamline your academic research process by automating interactions with Google Scholar. Instead of manually searching and copying information, this workflow directs the browser to perform targeted searches on your behalf. It then automatically extracts key data points from the resulting academic papers, articles, and citations. Finally, it gathers all this collected information and organizes it neatly into a structured spreadsheet. This saves you significant time and ensures your research data is organized and ready for immediate analysis.

What does Google Scholar Citation Harvester do?

This tool streamlines academic research by automating manual searches on Google Scholar. It systematically "harvests" key data from search results, including paper titles, author lists, publication years, and links. It then compiles this unstructured information into a clean, ready-to-analyze spreadsheet, saving you hours of manual data entry.

What data can you scrape from Google Scholar ?

This workflow is designed to extract the Research paper of different authors on the Google Scholar search results page for each entry.

Specifically, it can scrape the following data points for each research paper found:
Paper Title
Authors
Publication Year
Journal / Source
Citation Count
Paper Link
PDF Link

How to use Google Scholar Citation Harvester ?

Here are two options for the description, specifically highlighting the data points that the workflow extracts.

Option 1: Professional Summary (Good for a main description area)

The Google Scholar Citation Harvester automates the manual effort involved in academic data collection. It systematically navigates Google Scholar search results and extracts essential research metadata—including paper title, authors, publication year, journal or source, citation count, paper link, and direct PDF link—then compiles the data into a clean, structured spreadsheet ready for analysis, reporting, or literature review.

Option 2: Bulleted List (Best for quickly showing exactly what data is captured)

This workflow accelerates literature reviews by automatically extracting structured academic metadata from Google Scholar search results into a spreadsheet. It captures the following data points:

Paper Title
Authors
Publication Year
Journal / Source
Citation Count
Paper Link
PDF Link

Why scrape Google Scholar ?

This workflow targets Google Scholar because it is widely regarded as the most comprehensive and accessible free search engine specifically designed for academic literature.

Key reasons to use Google Scholar include:

Broad Scope: Unlike specialized databases limited to one field, Google Scholar indexes research across all disciplines, including peer-reviewed papers, theses, books, conference proceedings, and preprints from universities and repositories worldwide.
Citation Metrics: It provides crucial "Cited by" counts for every entry, offering an immediate indicator of a paper's impact and influence within the academic community.
Academic Focus: It filters out general web content (like news blogs or commercial sites), ensuring search results are highly relevant to serious research.
Direct Access: It excels at locating direct links to downloadable PDFs or institutional access points for full-text articles.

60-80credits per task (estimated)