# Semantic Scholar Scraper — Papers, Citations & TLDRs (`hipersoft/semantic-scholar-scraper`) Actor

Bulk-scrape academic papers from Semantic Scholar's 200M+ corpus: title, abstract, AI TLDR summary, authors, venue, year, citation & influential-citation counts, fields of study, DOI/PubMed/arXiv IDs and open-access PDF links. Filter by year, field and citations. Thousands per run. No login, no key.

- **URL**: https://apify.com/hipersoft/semantic-scholar-scraper.md
- **Developed by:** [hiper soft](https://apify.com/hipersoft) (community)
- **Categories:** Other
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.0004 / paper scraped

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 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/docs.md):

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

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

## Semantic Scholar Scraper — Papers, Citations

Bulk-scrape academic papers from **Semantic Scholar**, an AI-powered corpus of **200M+ papers** across every field. Get titles, abstracts, authors, venues, years, **citation and influential-citation counts**, fields of study, cross-IDs (DOI / PubMed / arXiv) and open-access PDF links. Filter by year, field of study and citation count. Thousands of papers per run. No account, no API key.

### Features

- 🔎 **Corpus-wide search** — 200M+ papers, all disciplines
- 📈 **Citation metrics** — total citations + **influential** citations + reference counts
- 🎓 **Filters** — year range, fields of study, minimum citations, open-access-only
- 🔗 **Cross-IDs** — DOI, PubMed and arXiv IDs for each paper, plus free PDF links
- 👥 **Authors with IDs**
- 📊 **Bulk & token-paginated** — scales to tens of thousands of papers per query

### What you get

One record per paper:

```json
{
  "paperId": "649def34f8be52c8b66281af98ae884c09aef38b",
  "title": "…",
  "year": 2023,
  "authors": [{ "name": "…", "authorId": "1741101" }],
  "venue": "NeurIPS",
  "citationCount": 1240,
  "influentialCitationCount": 210,
  "referenceCount": 42,
  "fieldsOfStudy": ["Computer Science"],
  "doi": "10.…",
  "pmid": null,
  "arxivId": "1706.03762",
  "openAccessPdfUrl": "https://…",
  "url": "https://www.semanticscholar.org/paper/…"
}
````

(`abstract` included when available.)

### Input

```json
{
  "query": "graph neural networks",
  "yearFrom": "2020",
  "fieldsOfStudy": ["Computer Science"],
  "minCitationCount": 10,
  "maxResults": 5000
}
```

| Field | Description |
|-------|-------------|
| `query` | Text search (required). |
| `yearFrom` / `yearTo` | Publication-year range. |
| `fieldsOfStudy` | Restrict to fields (Computer Science, Medicine…). |
| `minCitationCount` | Only papers with ≥ this many citations. |
| `openAccessOnly` | Only papers with a free PDF. |
| `maxResults` | Max papers to return. |
| `apiKey` | Optional S2 key for a higher rate limit. |

### Use cases

- **Literature reviews** — every paper on a topic, ranked by citations
- **Citation & impact analysis** — find the influential works and authors in a field
- **AI/ML datasets** — build corpora of titles + abstracts + metadata
- **Cross-referencing** — map papers across DOI, PubMed and arXiv

### Pricing

Pay-per-event: a small amount per paper scraped. See the **Pricing** tab for current rates.

### FAQ

**Do I need an API key?**
No. This Actor uses the public [Semantic Scholar](https://www.semanticscholar.org) Academic Graph API with no account required. You can optionally supply an S2 `apiKey` for a higher rate limit on very large runs.

**How many papers can I scrape per run?**
Set `maxResults` as high as you need — the API is token-paginated and scales to tens of thousands of papers per query.

**Is scraping Semantic Scholar legal?**
Yes. This Actor uses the official Academic Graph API and returns its openly available metadata as-is, with no login or scraping tricks.

**What format is the output?**
Structured JSON — one record per paper — exportable as JSON, CSV or Excel. Each record includes title, abstract (when available), authors, venue, year, citation and influential-citation counts, fields of study, cross-IDs (DOI/PubMed/arXiv) and open-access PDF links.

**Can I filter by year, field or citation count?**
Yes. Use `yearFrom`/`yearTo` for a publication-year range, `fieldsOfStudy` to restrict disciplines, `minCitationCount` to keep only well-cited papers, and `openAccessOnly` for papers with a free PDF.

### Related Actors

Building a citation or literature dataset? These other hipersoft scrapers pair well with this one:

- [OpenAlex Scraper](https://apify.com/hipersoft/openalex-scraper) — 250M+ scholarly works with citations, authors and abstracts
- [Crossref Scraper](https://apify.com/hipersoft/crossref-scraper) — DOIs, citation counts and metadata from 150M+ works
- [arXiv Papers Scraper](https://apify.com/hipersoft/arxiv-scraper) — preprints with full abstracts and PDF links
- [PubMed Scraper](https://apify.com/hipersoft/pubmed-scraper) — biomedical papers, abstracts and MeSH terms

### Notes

Uses the public Semantic Scholar Academic Graph API. Returns its openly-available metadata as-is. This is an independent tool and is not affiliated with or endorsed by Semantic Scholar or the Allen Institute for AI.

# Actor input Schema

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

Text search across the corpus (required by the bulk API). e.g. "graph neural networks", "crispr".

## `yearFrom` (type: `string`):

Earliest publication year (e.g. 2020). Optional.

## `yearTo` (type: `string`):

Latest publication year. Optional.

## `fieldsOfStudy` (type: `array`):

Filter to fields, e.g. Computer Science, Medicine, Biology.

## `minCitationCount` (type: `integer`):

Only papers with at least this many citations.

## `openAccessOnly` (type: `boolean`):

Only papers with a free open-access PDF.

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

Maximum papers to return (a broad query matches millions).

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

Optional S2 API key for a higher rate limit on large runs.

## Actor input object example

```json
{
  "query": "graph neural networks",
  "minCitationCount": 0,
  "openAccessOnly": false,
  "maxResults": 1000
}
```

# 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 = {
    "query": "graph neural networks"
};

// Run the Actor and wait for it to finish
const run = await client.actor("hipersoft/semantic-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 = { "query": "graph neural networks" }

# Run the Actor and wait for it to finish
run = client.actor("hipersoft/semantic-scholar-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 '{
  "query": "graph neural networks"
}' |
apify call hipersoft/semantic-scholar-scraper --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "Semantic Scholar Scraper — Papers, Citations & TLDRs",
        "description": "Bulk-scrape academic papers from Semantic Scholar's 200M+ corpus: title, abstract, AI TLDR summary, authors, venue, year, citation & influential-citation counts, fields of study, DOI/PubMed/arXiv IDs and open-access PDF links. Filter by year, field and citations. Thousands per run. No login, no key.",
        "version": "1.0",
        "x-build-id": "bYasSOLhxb0CedL9W"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/hipersoft~semantic-scholar-scraper/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-hipersoft-semantic-scholar-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": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/hipersoft~semantic-scholar-scraper/runs": {
            "post": {
                "operationId": "runs-sync-hipersoft-semantic-scholar-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/hipersoft~semantic-scholar-scraper/run-sync": {
            "post": {
                "operationId": "run-sync-hipersoft-semantic-scholar-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": [
                    "query"
                ],
                "properties": {
                    "query": {
                        "title": "Search query",
                        "type": "string",
                        "description": "Text search across the corpus (required by the bulk API). e.g. \"graph neural networks\", \"crispr\"."
                    },
                    "yearFrom": {
                        "title": "Year from",
                        "type": "string",
                        "description": "Earliest publication year (e.g. 2020). Optional."
                    },
                    "yearTo": {
                        "title": "Year to",
                        "type": "string",
                        "description": "Latest publication year. Optional."
                    },
                    "fieldsOfStudy": {
                        "title": "Fields of study",
                        "type": "array",
                        "description": "Filter to fields, e.g. Computer Science, Medicine, Biology.",
                        "items": {
                            "type": "string"
                        }
                    },
                    "minCitationCount": {
                        "title": "Min citations",
                        "minimum": 0,
                        "type": "integer",
                        "description": "Only papers with at least this many citations.",
                        "default": 0
                    },
                    "openAccessOnly": {
                        "title": "Open-access only",
                        "type": "boolean",
                        "description": "Only papers with a free open-access PDF.",
                        "default": false
                    },
                    "maxResults": {
                        "title": "Max results",
                        "minimum": 1,
                        "maximum": 100000,
                        "type": "integer",
                        "description": "Maximum papers to return (a broad query matches millions).",
                        "default": 1000
                    },
                    "apiKey": {
                        "title": "Semantic Scholar API key (optional)",
                        "type": "string",
                        "description": "Optional S2 API key for a higher rate limit on large runs."
                    }
                }
            },
            "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
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```