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

The current published implementation can return the following 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

• Ready-to-use workflow: The extraction steps for Google Scholar are already configured, so you do not need to build the scraper from scratch.
• Flexible execution: Run the ready-made task locally in the supported Octoparse environment.
• Structured, repeatable output: The same configured fields are returned as rows that are easier to compare, filter, deduplicate, and process than manually copied pages.
• Input guardrails: The current form exposes the verified inputs and limits needed by this template.
• Practical handoff: Review results in Octoparse and export or process the structured data in the formats supported by your Octoparse environment.

📝 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 the template and select Try it or Start.
2. Complete the input fields listed above.
3. Start the task using the supported local run mode.
4. Review the output rows and export or process the structured data.

⚠️ Limitations

Results depend on what the source site exposes at run time. A listed output field can be empty when the source page does not provide that value. Input limits shown above are enforced by the template.

💡 Tips

Use specific, valid inputs and review a representative result before starting a large batch. Remove duplicate inputs when repeated records are not needed.

❓ FAQ

How does this template work?

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.

What do I need to enter?

Use the fields and accepted values shown in the Input section. Only user-relevant limits are listed.

What data does this template return?

The current output fields and a representative JSON Data Preview are listed in the Output section. Field availability can vary when the source page does not display a value.

Is this template free to use?

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

Why can some output fields be empty?

Source pages do not always expose every value for every record, and page layouts can vary by item, market, or current site response. The template returns the field when the current page provides it.

Can I export the collected data?

You can review the structured rows in Octoparse and export or process them using the options supported by your Octoparse environment.

🔗 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.