Google Scholar Scraper

📌 What is a Google Scholar scraper?

This template searches Google Scholar by keyword and turns each search result into structured research data, including titles, authors, publication years, descriptions, article links, citation counts, related-article links, and available abstracts. It is useful for researchers, students, librarians, analysts, and research teams that need repeatable literature discovery without manually copying result pages.

Data is collected from Google Scholar. Google Scholar is a search service for scholarly literature, including articles, theses, books, abstracts, and court opinions from academic publishers, repositories, universities, and other research sources.

💰 Pricing

This template is currently free of charge and has no per-line usage fee. Octoparse plan or resource limits may still apply.

📦 Output

Google Scholar Scraper returns these fields:

• Title
• Author
• Published_year
• Description
• Article_Link
• Cited_for
• All_versions
• Related_articles_Link
• Current_page
• Full_Abstract

{
  "Title": "Data mining in education",
  "Author": "C Romero, S Ventura",
  "Published_year": "2013",
  "Description": "… The goal of text mining, also referred to as text data mining or text analytics, is to derive high-quality information from text. Typical text mining tasks include text categorization, text …",
  "Article_Link": "https://wires.onlinelibrary.wiley.com/doi/abs/10.1002/widm.1075",
  "Cited_for": "1347",
  "All_versions": "5",
  "Related_articles_Link": "https://scholar.google.com/scholar?q=related:M5gg5hmoDBcJ:scholar.google.com/&scioq=data+mining&hl=en&as_sdt=0,5",
  "Current_page": null,
  "Full_Abstract": null
}

🎯 Use Cases

• Build a literature-review dataset from titles, authors, publication years, descriptions, and article links.
• Compare citation counts and available versions to identify influential or widely distributed research.
• Track how the search landscape for a topic changes across repeated research snapshots.
• Create reading lists or research corpora for bibliometric, academic trend, and topic analysis.

🐙 Why Octoparse

• Built for Google Scholar: The template applies the selected Google Scholar language, submits each keyword, loops through the returned scholarly search results, and extracts the configured fields into one structured row per result.
• Inputs match the workflow: The form uses Keyword (up to 10,000 entries) and Language.
• Fields stay connected: Google Scholar Scraper returns Title, Article_Link, Description, Author, and Published_year in the same structured dataset.
• Ready for repeat use: After Google Scholar Scraper runs locally, schedule eligible tasks and export the rows for spreadsheets, dashboards, APIs, or AI workflows.

📝 Input

Complete the following fields:

• Language (Required) — Select a language for Google Scholar search. Available options: 한국어, 日本語, 中文 (繁體), Català, Čeština, Dansk, English, Français, Filipino, Hrvatski, Deutsch, Español, Indonesia, Latviešu, Magyar, Lietuvių, Italiano, Norsk, Polski, Português (Brasil), Português (Portugal), Nederlands, Română, Svenska, Slovenčina, Suomi, Tiếng Việt, Slovenščina, Türkçe, Ελληνικά, Български, Русский, עברית‎, ﺎﻠﻋﺮﺒﻳﺓ‎, ﻑﺍﺮﺳی‎, हिन्दी, Српски, ไทย, Українська.
• Keyword (Required) — Enter a list of keywords for searching Google Scholar. Up to 10,000 entries per run.

🚀 How to Use

1. Open Google Scholar Scraper and click Try it!.
2. Complete Keyword and Language using the formats and limits shown in the Input section.
3. Run it locally in Octoparse and start the task.
4. Review fields such as Title, Article_Link, and Description, then export the rows in the format you need.

💡 Tips

• Start with a focused Keyword so the first run is easy to review before widening the search.
• Use Title and Article_Link when checking duplicates or comparing repeated exports.

❓ FAQ

How many entries can Google Scholar Scraper accept in Keyword per run?

Enter up to 10,000 values in Keyword per run.

Which Google Scholar pages does Google Scholar Scraper process?

The workflow is configured for search-result pages and returns fields such as Title, Article_Link, Description, and Author.

What can I use data from Google Scholar Scraper for?

Build a literature-review dataset from titles, authors, publication years, descriptions, and article links.

🔗 Related Templates

• Google Scholar Scraper (Cloud) — Use the cloud version for the same Google Scholar source when cloud execution better fits the workflow.
• Google Scholar Scraper (Batch Generate URL) — Use the batch URL workflow when you want to generate or process Google Scholar result URLs in batches.