# OpenAlex Scraper - 250M Papers & Citations (`antishock/openalex-academic-works-scraper`) Actor

Scrape OpenAlex for 250M+ academic papers, citations, authors, and institutions. Extract research metadata for bibliometric analysis, literature reviews, and academic trend mapping.

- **URL**: https://apify.com/antishock/openalex-academic-works-scraper.md
- **Developed by:** [Ryan Zinburg](https://apify.com/antishock) (community)
- **Categories:** Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.00 / 1,000 result exporteds

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/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## OpenAlex Academic Works Scraper

Extract research papers, citations, author profiles and institutional data from OpenAlex - the world's largest open academic database with 250M+ works, free to access.

### Features

- Search by keyword, author, institution, journal or DOI
- Filter by field of study, publication year, citation count, open access status
- Returns: title, abstract, authors, institutions, journal, DOI, publication date, citation count, reference list, open access URL
- Access data going back to the 1800s
- No API key required

### Input Example

```json
{
  "searchQuery": "transformer neural network attention",
  "fieldOfStudy": "Computer Science",
  "yearFrom": 2020,
  "minCitations": 100,
  "maxResults": 500
}
```

### Output Example

```json
{
  "title": "Attention Is All You Need",
  "authors": ["Ashish Vaswani", "Noam Shazeer"],
  "institutions": ["Google Brain", "Google Research"],
  "journal": "Advances in Neural Information Processing Systems",
  "doi": "10.48550/arXiv.1706.03762",
  "publishedYear": 2017,
  "citationCount": 98432,
  "openAccessUrl": "https://arxiv.org/abs/1706.03762"
}
```

### Use Cases

- Academic literature review at scale
- Citation network analysis
- University research performance benchmarking
- Grant proposal background research
- AI training datasets from academic literature

### Pricing

$0.001 per work/paper scraped.

# Actor input Schema

## `searchQuery` (type: `string`):

Keyword search query, e.g. machine learning healthcare or CRISPR gene editing.

## `filterConcept` (type: `string`):

Optional OpenAlex concept ID filter, e.g. C154945302.

## `filterYear` (type: `string`):

Optional year or range, e.g. 2024 or 2020-2024.

## `filterOpenAccess` (type: `boolean`):

Only return open access works.

## `sortBy` (type: `string`):

Sort works by citation count or publication date.

## `maxResults` (type: `integer`):

Maximum number of works to export.

## `includeAbstract` (type: `boolean`):

Reconstruct abstract text from OpenAlex abstract\_inverted\_index.

## Actor input object example

```json
{
  "searchQuery": "machine learning",
  "filterConcept": "",
  "filterYear": "",
  "filterOpenAccess": false,
  "sortBy": "cited_by_count",
  "maxResults": 100,
  "includeAbstract": 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 = {
    "searchQuery": "machine learning"
};

// Run the Actor and wait for it to finish
const run = await client.actor("antishock/openalex-academic-works-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 = { "searchQuery": "machine learning" }

# Run the Actor and wait for it to finish
run = client.actor("antishock/openalex-academic-works-scraper").call(run_input=run_input)

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

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

```

## CLI example

```bash
echo '{
  "searchQuery": "machine learning"
}' |
apify call antishock/openalex-academic-works-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=antishock/openalex-academic-works-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/Cdf2dx5w3rUtRpEch/builds/XcqnY6N73COCjIChs/openapi.json