Google scholar scraper
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Extract scholarly results from a Google Scholar page and export paper titles, citations, authors, and publication details in CSV for faster research.
Extract Scholar Data for ResearchUse Thunderbit to scrape Google Scholar pages and collect paper titles, citations, authors, and publication details with a simple workflow. Save time on academic research with structured exports and no coding.
Install fromChrome Web Store
Extract Scholar Data for Research
Thunderbit can scrape data from websites, including subpages, PDFs, docs, and images, then structure it into clean fields for research workflows.
It can also summarize, categorize, and format extracted information, then export it to Google Sheets, Airtable, or Notion for easy review and analysis.
How to Extract Google Scholar Data Using Thunderbit
STEP 1Download and InstallDownload and install the Thunderbit Chrome Extension from the Thunderbit Chrome Extension Download Page. Once installed, log in or create a free account to get started.
STEP 2Open ExtensionGo to the Google Scholar search results page, author profile, or publication list that you want to scrape. Open the Thunderbit Chrome Extension, choose the Google Scholar scraper, and enter a valid Google Scholar page URL in the URL field.
STEP 3Click the Extract Google Scholar Data ButtonClick the Extract Google Scholar Data button. Thunderbit will read the page and extract paper titles, citation counts, authors, and publication details into a structured table. When the scrape is complete, download the CSV file and use it in Excel, Google Sheets, Airtable, or Notion.
Learn how to extract Google Scholar data
Extract Paper Details from Google Scholar
This tool pulls bibliographic data from a Google Scholar URL and turns it into a clean CSV table. It captures paper titles, citation counts, authors, and publication details from search results, author profiles, or publication lists. It is built for researchers and students who want to collect academic references faster without copying each entry by hand.
Organize Scholarly Results into Structured CSV Data
The scraper converts Google Scholar pages into structured rows, making academic research easier to review and compare. Each record is organized with the key citation fields you need, so you can sort papers, analyze impact, or build a reading list with less manual work. It helps reduce errors and keeps scholarly data in a format that is ready for spreadsheet analysis.
Export Research Data for Academic Workflows
After extraction, the results are delivered as a downloadable CSV file that can be opened in Excel or other spreadsheet tools. This makes it easy to manage references, prepare literature reviews, or share findings with classmates and colleagues. The standard table format also supports quick filtering, sorting, and citation tracking for ongoing academic projects.
Support Research, Literature Reviews, and Citation Tracking
Researchers can use this tool to gather paper lists from search results, while students can quickly collect sources for assignments and theses. It is also useful for tracking citation counts across publications and reviewing author information from scholar profiles. By automating collection from a valid Google Scholar page, it saves time and supports more organized academic research.
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What users say about Thunderbit
Taryn W.Growth Strategist@Thunderbit changed how I run competitor research. I click 'AI Suggest Fields,' and it builds a clean table across paginated results—no coding, no CSS. Huge time-saver when analyzing product data from long-tail marketplaces.
Miles T.Sales Development ConsultantI use Thunderbit to grab emails and phone numbers from directories. It extracts clean contact info in one click, and exporting to Sheets or Notion takes seconds. No extra setup, no coding—just usable data ready to work with.
Rhea C.E-commerce AnalystThunderbit helps me monitor SKU data across multiple pages. I scrape the listings, then use Subpage Scraping to pull full product specs, pricing, reviews, and stock. The AI organizes everything into columns I define.
Cassian B.Real Estate AdvisorThunderbit's Scheduled Scraper makes real estate tracking easier. I describe the interval in plain English, and it automatically pulls updated listings, prices, and links without touching the setup again. Simple and very practical.
Dorian B.Content & SEO SpecialistI use Thunderbit's Field AI Prompts to clean and tag scraped blog content. It extracts titles, authors, and even suggests categories. Works great across dynamic sites and subpages—perfect for building structured SEO datasets.
Lina K.Marketplace Operations LeadWe track SKUs from niche stores using Thunderbit. Cloud Scraping handles 50 pages at a time, and for login-required sites, we switch to browser mode. It’s fast, flexible, and doesn’t need ongoing maintenance or manual edits.
Jorge F.Inbound Sales ManagerThunderbit’s AI Autofill is a lifesaver. After scraping contact info, I use it to fill lead forms directly in my browser. I just select the tab, and it fills everything using the scraped row. No manual input needed.
Alina D.Freelance ResearcherI rely on Thunderbit for extracting data from PDFs, image-based sites, and infinite scroll pages. It handles messy formats with AI and delivers ready-to-export tables I can send to Google Sheets or Airtable in seconds.
Taryn W.Growth Strategist@Thunderbit changed how I run competitor research. I click 'AI Suggest Fields,' and it builds a clean table across paginated results—no coding, no CSS. Huge time-saver when analyzing product data from long-tail marketplaces.
Miles T.Sales Development ConsultantI use Thunderbit to grab emails and phone numbers from directories. It extracts clean contact info in one click, and exporting to Sheets or Notion takes seconds. No extra setup, no coding—just usable data ready to work with.
Rhea C.E-commerce AnalystThunderbit helps me monitor SKU data across multiple pages. I scrape the listings, then use Subpage Scraping to pull full product specs, pricing, reviews, and stock. The AI organizes everything into columns I define.
Cassian B.Real Estate AdvisorThunderbit's Scheduled Scraper makes real estate tracking easier. I describe the interval in plain English, and it automatically pulls updated listings, prices, and links without touching the setup again. Simple and very practical.
Dorian B.Content & SEO SpecialistI use Thunderbit's Field AI Prompts to clean and tag scraped blog content. It extracts titles, authors, and even suggests categories. Works great across dynamic sites and subpages—perfect for building structured SEO datasets.
Lina K.Marketplace Operations LeadWe track SKUs from niche stores using Thunderbit. Cloud Scraping handles 50 pages at a time, and for login-required sites, we switch to browser mode. It’s fast, flexible, and doesn’t need ongoing maintenance or manual edits.
Jorge F.Inbound Sales ManagerThunderbit’s AI Autofill is a lifesaver. After scraping contact info, I use it to fill lead forms directly in my browser. I just select the tab, and it fills everything using the scraped row. No manual input needed.
Alina D.Freelance ResearcherI rely on Thunderbit for extracting data from PDFs, image-based sites, and infinite scroll pages. It handles messy formats with AI and delivers ready-to-export tables I can send to Google Sheets or Airtable in seconds.