# Semantic Scholar Citations Scraper (`parseforge/semanticscholar-citations-scraper`) Actor

Query Semantic Scholar for the full citation graph of any paper. Records carry paper ID, citing paper ID, title, authors, year, venue, citation intent, context count, influential flag, and DOI. Useful for literature reviews, impact analysis, and academic mapping.

- **URL**: https://apify.com/parseforge/semanticscholar-citations-scraper.md
- **Developed by:** [ParseForge](https://apify.com/parseforge) (community)
- **Categories:** Education, Automation, Integrations
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet

## Pricing

from $7.50 / 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.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

## What's an Apify Actor?

Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.

In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):

```bash
npm install apify-client
```

In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):

```bash
pip install apify-client
```

In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):

````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash

In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).

If your project is in a different language, use 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

![ParseForge Banner](https://github.com/ParseForge/apify-assets/blob/ad35ccc13ddd068b9d6cba33f323962e39aed5b2/banner.jpg?raw=true)

## 🔗 Semantic Scholar Citations Scraper

> 🚀 **Export Semantic Scholar citations and references for any paper in seconds. Clean tabular records, ready for download.**

> 🕒 **Last updated:** 2026-06-05 · **📊 12 fields** per record · Public API · No login required

The Semantic Scholar Citations Scraper turns the public Semantic Scholar graph API into a flat dataset of citing papers (or references), with citation intent, contexts, and influence flags.

Filter the source, pick how many rows you want, and download.

| 🎯 Target Audience | 💡 Primary Use Cases |
|---|---|
| 🧑‍🔬 Researchers | Pull a clean dataset for downstream analysis |
| 👩‍💻 Developers | Mirror the API into your own database |
| 🏢 Data teams | Snapshot metadata on a schedule |
| 📰 Journalists | Verify claims against the source of record |

### 📋 What the Semantic Scholar Citations Scraper does

- Calls the public endpoint with the parameters you supply.
- Parses each record into a flat row.
- Casts numeric fields to numbers.
- Surfaces upstream rate limits as a clean error record.
- Exports to every Apify dataset download format.

> 💡 **Why it matters.** A flat tabular shape drops straight into pandas, BigQuery, or a Google Sheet without further wrangling.

### 🎬 Full Demo

_🚧 Coming soon._

### ⚙️ Input

<table>
<tr><th>Field</th><th>Type</th><th>Required</th><th>Description</th></tr>
<tr><td><code>paperId</code></td><td>string</td><td>Yes</td><td>Semantic Scholar paper ID, DOI, arXiv ID, or URL.</td></tr>
<tr><td><code>mode</code></td><td>enum</td><td>No</td><td>Citations or references.</td></tr>
<tr><td><code>maxItems</code></td><td>integer</td><td>No</td><td>Free 10, paid up to 1,000,000.</td></tr>
<tr><td><code>apiKey</code></td><td>secret string</td><td>No</td><td>Optional Semantic Scholar API key for higher rate limits.</td></tr>
</table>

**Example 1, citations of attention-is-all-you-need:**
```json
{
  "paperId": "10.48550/arXiv.1706.03762",
  "mode": "citations",
  "maxItems": 50
}
````

**Example 2, references of a paper:**

```json
{
  "paperId": "DOI:10.1038/nature14539",
  "mode": "references"
}
```

> ⚠️ **Good to Know.** The upstream public API may rate-limit aggressive callers. The actor surfaces rate-limit notes as a clean error record instead of crashing.

### 📊 Output

Each record is a flat object.

| Field | Type | Description |
|---|---|---|
| 🆔 `paperId` | string | Source paper ID. |
| 🆔 `citingPaperId` | string | Citing or cited paper ID. |
| 📝 `title` | string | Paper title. |
| 👥 `authors` | string | Comma-separated authors. |
| 📅 `year` | number | Publication year. |
| 🏛️ `venue` | string | Publication venue. |
| 🎯 `intent` | string | Citation intent (background, method, result). |
| 🔢 `contextsCount` | number | Number of citation contexts. |
| ⭐ `influential` | boolean | Whether the citation is flagged as influential. |
| 🔗 `doi` | string | DOI of citing or cited paper. |
| 🕒 `scrapedAt` | string | When this row was fetched. |
| ❌ `error` | string | Set if the upstream response was an error. |

### ✨ Why choose this Actor

| 🆓 | Free to try, no signup needed. |
| 🧹 | Clean column names ready for BI tools. |
| 🔢 | Numeric casting handled for you. |
| 🛟 | Rate-limit notes surface as a single error record. |
| 🔍 | Filter the source through the input schema. |
| 💾 | Push to dataset, instant tabular export. |

### 📈 How it compares to alternatives

| Approach | Setup time | Clean schema | Filters | Rate-limit handling |
|---|---|---|---|---|
| Roll your own fetch | 30+ minutes | manual | manual | manual |
| **This Actor** | 5 seconds | ✅ | ✅ | ✅ |

### 🚀 How to use

1. Click **Try for free**.
2. Adjust the inputs to match your query.
3. Click **Start**. Your dataset is ready in seconds.

### 💼 Business use cases

**📊 Market intelligence.** Snapshot the catalog and track new entries week over week.

**🤖 ML feature engineering.** Build a clean training set from public records.

**📰 Newsroom fact-checking.** Verify claims in 30 seconds.

**🏢 Procurement.** Pipe records straight into your warehouse.

### 🔌 Automating Semantic Scholar Citations Scraper

- Make and Zapier. Trigger on a schedule, push to Airtable or Google Sheets.
- Apify scheduler. Run it daily, weekly, or on demand.
- Webhooks. POST to your endpoint when a run finishes.
- Pipe to BigQuery, Snowflake, Postgres via native Apify integrations.

### 🌟 Beyond business use cases

**🎓 Education.** Use real public datasets for coursework.

**🧪 Personal research.** Track topics that matter to you.

**🤝 Non-profit and open data.** Build public dashboards without writing scrapers.

**🧰 Tinkering.** Spin up a dataset to test a new chart library or notebook idea.

### 🤖 Ask an AI assistant about this scraper

Pop this README into ChatGPT, Claude, or any AI assistant and ask it to map your workflow to the actor's inputs. The schema, examples, and field list above contain everything an LLM needs to design a working pipeline.

### ❓ Frequently Asked Questions

**❓ Do I need an API key.** No. The Semantic Scholar endpoint used here is public.

**❓ Can I filter the source.** Yes. See the input schema for the filters available.

**❓ Can I schedule runs.** Yes, use the Apify native scheduler.

**❓ Is this scraping or API.** API. The endpoint is fully public.

**❓ Will the schema change.** Core fields are stable. Optional fields surface as null when the source omits them.

**❓ What format can I download.** Every Apify dataset download format from the dataset UI.

**❓ How do you handle rate limits.** A clean error record is pushed to the dataset.

**❓ Can I run partial pulls.** Yes, set maxItems to the size you need.

**❓ Is it free.** Free tier gives you 10 records, paid plans up to 1,000,000.

**❓ Does the actor cache results.** No, every run hits the live endpoint.

### 🔌 Integrate with any app

Apify ships native integrations with Make, Zapier, Slack, Discord, Google Drive, Google Sheets, Gmail, Airbyte, Keboola, Telegram, GitHub, and any REST API or webhook endpoint.

### 🔗 Recommended Actors

| Actor | What it does |
|---|---|
| [ParseForge OpenAlex Works Scraper](https://apify.com/parseforge/openalex-works-scraper) | 250M+ scholarly works. |
| [ParseForge Papers With Code SOTA Scraper](https://apify.com/parseforge/papers-with-code-sota-scraper) | State-of-the-art benchmark tracking. |
| [ParseForge Open LLM Leaderboard Scraper](https://apify.com/parseforge/openllm-leaderboard-scraper) | Hugging Face Open LLM Leaderboard. |
| [ParseForge OurAirports Scraper](https://apify.com/parseforge/ourairports-scraper) | Global airport database. |

> 💡 **Pro Tip.** Browse the complete [ParseForge collection](https://apify.com/parseforge) for 900+ production-grade scrapers across business intelligence, real estate, e-commerce, sports, finance, and public records.

***

**Disclaimer.** This actor scrapes only publicly available data. ParseForge is not affiliated with, endorsed by, or sponsored by any of the third-party services referenced. Users are responsible for complying with the target site's terms of service and applicable law. [Create a free account w/ $5 credit](https://console.apify.com/sign-up?fpr=vmoqkp).

# Actor input Schema

## `paperId` (type: `string`):

Semantic Scholar paper ID, DOI, arXiv ID, or URL. Required.

## `mode` (type: `string`):

Citations (papers citing this one) or references (papers this one cites).

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

Free users limited to 10 items (preview). Paid users optional, max 1,000,000.

## `apiKey` (type: `string`):

Optional API key for higher rate limits. Get one at semanticscholar.org/product/api.

## Actor input object example

```json
{
  "mode": "citations",
  "maxItems": 10
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# 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": 10
};

// Run the Actor and wait for it to finish
const run = await client.actor("parseforge/semanticscholar-citations-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": 10 }

# Run the Actor and wait for it to finish
run = client.actor("parseforge/semanticscholar-citations-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 '{
  "maxItems": 10
}' |
apify call parseforge/semanticscholar-citations-scraper --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "Semantic Scholar Citations Scraper",
        "description": "Query Semantic Scholar for the full citation graph of any paper. Records carry paper ID, citing paper ID, title, authors, year, venue, citation intent, context count, influential flag, and DOI. Useful for literature reviews, impact analysis, and academic mapping.",
        "version": "0.1",
        "x-build-id": "x41pNdk7hl5CqUnFT"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/parseforge~semanticscholar-citations-scraper/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-parseforge-semanticscholar-citations-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/parseforge~semanticscholar-citations-scraper/runs": {
            "post": {
                "operationId": "runs-sync-parseforge-semanticscholar-citations-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK",
                        "content": {
                            "application/json": {
                                "schema": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/parseforge~semanticscholar-citations-scraper/run-sync": {
            "post": {
                "operationId": "run-sync-parseforge-semanticscholar-citations-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        }
    },
    "components": {
        "schemas": {
            "inputSchema": {
                "type": "object",
                "required": [
                    "paperId"
                ],
                "properties": {
                    "paperId": {
                        "title": "Paper ID",
                        "type": "string",
                        "description": "Semantic Scholar paper ID, DOI, arXiv ID, or URL. Required."
                    },
                    "mode": {
                        "title": "Mode",
                        "enum": [
                            "citations",
                            "references"
                        ],
                        "type": "string",
                        "description": "Citations (papers citing this one) or references (papers this one cites).",
                        "default": "citations"
                    },
                    "maxItems": {
                        "title": "Max Items",
                        "minimum": 1,
                        "maximum": 1000000,
                        "type": "integer",
                        "description": "Free users limited to 10 items (preview). Paid users optional, max 1,000,000."
                    },
                    "apiKey": {
                        "title": "Semantic Scholar API key (optional)",
                        "type": "string",
                        "description": "Optional API key for higher rate limits. Get one at semanticscholar.org/product/api."
                    }
                }
            },
            "runsResponseSchema": {
                "type": "object",
                "properties": {
                    "data": {
                        "type": "object",
                        "properties": {
                            "id": {
                                "type": "string"
                            },
                            "actId": {
                                "type": "string"
                            },
                            "userId": {
                                "type": "string"
                            },
                            "startedAt": {
                                "type": "string",
                                "format": "date-time",
                                "example": "2025-01-08T00:00:00.000Z"
                            },
                            "finishedAt": {
                                "type": "string",
                                "format": "date-time",
                                "example": "2025-01-08T00:00:00.000Z"
                            },
                            "status": {
                                "type": "string",
                                "example": "READY"
                            },
                            "meta": {
                                "type": "object",
                                "properties": {
                                    "origin": {
                                        "type": "string",
                                        "example": "API"
                                    },
                                    "userAgent": {
                                        "type": "string"
                                    }
                                }
                            },
                            "stats": {
                                "type": "object",
                                "properties": {
                                    "inputBodyLen": {
                                        "type": "integer",
                                        "example": 2000
                                    },
                                    "rebootCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "restartCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "resurrectCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "computeUnits": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            },
                            "options": {
                                "type": "object",
                                "properties": {
                                    "build": {
                                        "type": "string",
                                        "example": "latest"
                                    },
                                    "timeoutSecs": {
                                        "type": "integer",
                                        "example": 300
                                    },
                                    "memoryMbytes": {
                                        "type": "integer",
                                        "example": 1024
                                    },
                                    "diskMbytes": {
                                        "type": "integer",
                                        "example": 2048
                                    }
                                }
                            },
                            "buildId": {
                                "type": "string"
                            },
                            "defaultKeyValueStoreId": {
                                "type": "string"
                            },
                            "defaultDatasetId": {
                                "type": "string"
                            },
                            "defaultRequestQueueId": {
                                "type": "string"
                            },
                            "buildNumber": {
                                "type": "string",
                                "example": "1.0.0"
                            },
                            "containerUrl": {
                                "type": "string"
                            },
                            "usage": {
                                "type": "object",
                                "properties": {
                                    "ACTOR_COMPUTE_UNITS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_WRITES": {
                                        "type": "integer",
                                        "example": 1
                                    },
                                    "KEY_VALUE_STORE_LISTS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_INTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_EXTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_SERPS": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            },
                            "usageTotalUsd": {
                                "type": "number",
                                "example": 0.00005
                            },
                            "usageUsd": {
                                "type": "object",
                                "properties": {
                                    "ACTOR_COMPUTE_UNITS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_WRITES": {
                                        "type": "number",
                                        "example": 0.00005
                                    },
                                    "KEY_VALUE_STORE_LISTS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_INTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_EXTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_SERPS": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```