# Google Scholar Scraper (`easyapi/google-scholar-scraper`) Actor

Powerful Google Scholar scraper collect up to 5000 scholarly results per run  with flexible search options, citation filtering. Perfect for academic research, bibliometric analysis, and scientific trend tracking. 🎓🔍

- **URL**: https://apify.com/easyapi/google-scholar-scraper.md
- **Developed by:** [EasyApi](https://apify.com/easyapi) (community)
- **Categories:** Other
- **Features:** Limited permissions
- **Stats:** 464 total users, 18 monthly users, 100.0% runs succeeded, 8 bookmarks
- **User rating**: 2.55 out of 5 stars

## Pricing

from $4.99 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Google Scholar Scraper 🎓🔍

Effortlessly scrape academic data from Google Scholar with this powerful and flexible Actor! 🚀

### Features ✨

- 📚 Scrape scholarly articles, papers, and citations
- 🔢 Retrieve up to 5000 results per run
- 🌐 Support for multiple countries and languages
- ⏳ Time-based filtering options
- 💾 Results saved directly to your Apify dataset

### Use Cases 💡

- 🧪 Academic research and literature reviews
- 📊 Bibliometric analysis and citation tracking
- 🏫 University and research institution benchmarking
- 🔬 Trend analysis in scientific publications
- 👨‍🔬 Author and researcher profiling

### How It Works 🛠️

1. Set your search parameters in the input
2. The Actor fetch Google Scholar data
3. Results are processed and saved to your Apify dataset
4. Repeat until the desired number of results is reached or all available data is collected

### Input Parameters 📝

- `maxItems`: Maximum number of results to collect (100-5000)
- `query`: Your search term
- `gl`: Google country code (e.g., "us" for United States)
- `hl`: Interface language (e.g., "en" for English)
- `lr`: Language of search results (e.g., "lang_en" for English)
- `cr`: Country restriction for search results
- `nfpr`: No auto-correction of spelling (0 or 1)
- `filter`: Whether to filter similar results (0 or 1)
- `scholar_include_citations`: Include citations in results (true/false)
- `scholar_year_min`: Minimum year for results
- `scholar_year_max`: Maximum year for results
- `scholar_patents_courts`: Filter for patents and court cases
- `scisbd`: Scholar sort parameter (1 or 2)

### Output 📊

The Actor provides detailed information about each scholarly result, including:

- Title
- Authors
- Publication info
- Number of citations
- Link to the article
- Brief summary or abstract
- And more!

Get started with Google Scholar Scraper today and unlock valuable academic insights for your research projects! 🚀🎓

#### Input Example

A full explanation of an input example in JSON.

```
{
    "maxItems": 100,
    "query": "rocket" 
}
```

#### Output sample

The results will be wrapped into a dataset which you can always find in the **Storage** tab. Here's an excerpt from the data you'd get if you apply the input parameters above:

And here is the same data but in JSON. You can choose in which format to download your data: JSON, JSONL, Excel spreadsheet, HTML table, CSV, or XML.

```
[
	{
        "position": 1,
        "title": "Liquid-propellant rocket engine throttling: A comprehensive review",
        "link": "https://arc.aiaa.org/doi/abs/10.2514/1.49791",
        "domain": "arc.aiaa.org",
        "displayed_link": "MJ Casiano, JR Hulka, V Yang - Journal of propulsion and power, 2010 - arc.aiaa.org",
        "pdf_link": "https://ntrs.nasa.gov/api/citations/20090037061/downloads/20090037061.pdf",
        "snippet": "… and dynamics of an liquid-propellant rocket engine as well as difficulties and … rocket engine \nthrottling centered around engines from the United States. Several liquid-propellant rocket …",
        "cited_by_count": 253,
        "cited_by_link": "https://www.google.com/scholar?cites=7502999951619349366&as_sdt=2005&sciodt=0,5&hl=fr",
        "versions_count": 11,
        "versions_link": "https://www.google.com/scholar?cluster=7502999951619349366&hl=fr&as_sdt=0,5"
    },
    {
        "position": 2,
        "title": "Knowledge management–not rocket science",
        "link": "https://www.emerald.com/insight/content/doi/10.1108/13673270510590191/full/html",
        "domain": "www.emerald.com",
        "displayed_link": "D Call - Journal of Knowledge management, 2005 - emerald.com",
        "pdf_link": "http://j.pelet.free.fr/publications/km/Knowledge_management_not_rocket_science.pdf",
        "snippet": "Purpose – To provide a broad understanding of knowledge management and how to \nsuccessfully implement knowledge management. Design/methodology/approach – Using a wide …",
        "cited_by_count": 198,
        "cited_by_link": "https://www.google.com/scholar?cites=1591768766360518117&as_sdt=2005&sciodt=0,5&hl=fr",
        "versions_count": 7,
        "versions_link": "https://www.google.com/scholar?cluster=1591768766360518117&hl=fr&as_sdt=0,5"
    },
    ...
]
```

# Actor input Schema

## `maxItems` (type: `integer`):

Maximum number of scholarly results to be extracted.

## `query` (type: `string`):

The search term to use

## `gl` (type: `string`):

The Google country to use for the query

## `scholar_include_citations` (type: `boolean`):

Whether to include citations in scholar results.

## `scholar_year_min` (type: `integer`):

Minimum year for scholar results.

## `scholar_year_max` (type: `integer`):

Maximum year for scholar results.

## `scholar_patents_courts` (type: `string`):

Filter for patents and courts in scholar results.

## `scisbd` (type: `string`):

Sort parameter for scholar results.

## `hl` (type: `string`):

The Google UI language to return results

## `lr` (type: `string`):

Limit the results to a specific language

## `cr` (type: `string`):

Limit the results to a specific country

## `nfpr` (type: `integer`):

Exclude results from auto-corrected queries (0 or 1)

## `filter` (type: `integer`):

Enable/disable Similar Results and Omitted Results filters (0 or 1)

## Actor input object example

```json
{
  "maxItems": 1000,
  "query": "rocket",
  "scholar_include_citations": true
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "maxItems": 1000,
    "query": "rocket"
};

// Run the Actor and wait for it to finish
const run = await client.actor("easyapi/google-scholar-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "maxItems": 1000,
    "query": "rocket",
}

# Run the Actor and wait for it to finish
run = client.actor("easyapi/google-scholar-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "maxItems": 1000,
  "query": "rocket"
}' |
apify call easyapi/google-scholar-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,easyapi/google-scholar-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/QE5aLx6lA6uGUXesU/builds/GqGM8mHgPahOzq5DV/openapi.json