Google Scholar Scraper

A robust, high-performance utility designed for developer automation, data integration, and AI training. Features built-in captcha bypass, headful/headless browser execution, and proxy support to scrape Google data seamlessly, reliably, and at scale.

Pricing

from $4.99 / 1,000 results

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👁 codingfrontend

codingfrontend

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a month ago

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Features

Academic Papers: Extracts research papers and academic articles from Google Scholar search results
Citations Count: Captures how many times each paper has been cited by other works
Author Information: Records the names of all authors for each paper
Publication Venue: Extracts the journal or conference where the paper was published
Publication Year: Captures the year each paper was published
PDF Links: Collects direct PDF links when available for open-access papers
Text Snippets: Retrieves descriptive text snippets shown in Google Scholar results
Date Range Filtering: Filter papers by publication year range (yearFrom and yearTo)
Sort Options: Sort results by relevance or publication date
Proxy Support: Built-in Apify Proxy with residential proxies to avoid Scholar rate limiting

Input Parameters

Parameter	Type	Required	Default	Description
`query`	String	Yes	`"machine learning"`	Academic search query to look up on Google Scholar
`maxItems`	Integer	No	`50`	Maximum number of results to retrieve (1–10000)
`yearFrom`	Integer	No	—	Filter results published from this year onwards (e.g., 2020)
`yearTo`	Integer	No	—	Filter results published up to this year (e.g., 2024)
`sortBy`	String	No	`"relevance"`	Sort results by: `relevance` or `date`
`proxyConfiguration`	Object	No	Apify Residential	Proxy settings for the scraper

Input Schema Example

{
"query":"deep learning natural language processing",
"maxItems":100,
"yearFrom":2020,
"yearTo":2025,
"sortBy":"date",
"proxyConfiguration":{
"useApifyProxy":true,
"apifyProxyGroups":["RESIDENTIAL"]
}
}

Output Schema

The scraper outputs structured JSON data for each academic paper found on Google Scholar.

Main Fields

Field	Type	Description
`position`	Integer	Result position in search results
`title`	String	Paper title
`link`	String	URL to the paper
`authors`	String	Paper authors
`publication`	String	Publication venue (journal, conference, etc.)
`year`	Integer	Publication year
`citedBy`	Integer	Number of citations
`snippet`	String	Text snippet from the paper
`pdfLink`	String	Direct link to PDF if available
`searchQuery`	String	The search query used
`searchUrl`	String	Google Scholar search URL
`scrapedAt`	String	ISO timestamp of when the data was scraped

Academic Paper Example

{
"position":1,
"title":"Attention Is All You Need",
"link":"https://arxiv.org/abs/1706.03762",
"authors":"A Vaswani, N Shazeer, N Parmar, J Uszkoreit",
"publication":"Advances in neural information processing systems, 2017",
"year":2017,
"citedBy":98450,
"snippet":"The dominant sequence transduction models are based on complex recurrent or convolutional neural networks that include an encoder and a decoder...",
"pdfLink":"https://arxiv.org/pdf/1706.03762",
"searchQuery":"deep learning natural language processing",
"searchUrl":"https://scholar.google.com/scholar?q=deep+learning+natural+language+processing",
"scrapedAt":"2025-01-15T10:30:00.000Z"
}