# Google Fact Check Scraper (`seemuapps/google-fact-check-scraper`) Actor Search Google's Fact Check Tools database for claims and their reviews publisher, rating, source URL and export them to a clean dataset. - **URL**: https://apify.com/seemuapps/google-fact-check-scraper.md - **Developed by:** [Andrew](https://apify.com/seemuapps) (community) - **Categories:** SEO tools, Developer tools, Agents - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 claim reviews 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.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 ## Google Fact Check Scraper Search Google's Fact Check Tools database — the same index that powers Google's fact-check labels — and export every reviewed claim, the publisher, the rating, and the review URL to a clean dataset. ### What you get - **One dataset row per claim review** with claim text, claimant, claim date, publisher name, publisher site, review title, review URL, review date, textual rating, and language - **Multi-query** — pass a list of topics, people, or claim phrasings and get one consolidated dataset - **Filter by publisher** — restrict to a single fact-checker site (Snopes, PolitiFact, FactCheck.org, AFP, Reuters Fact Check, etc.) - **Filter by recency** — limit to claims reviewed within the last N days - **Multilingual** — restrict by language code or pull every language - **Auto-pagination** — the actor walks the API's `nextPageToken` chain until your result cap is hit ### Use cases - **Misinformation research** — pull every fact-checked claim about a topic, candidate, or event - **Journalism prep** — surface what fact-checkers have already covered before publishing - **AI trust & safety** — build a labelled dataset of claims with verdicts for model evaluation or RAG grounding - **Brand and reputation monitoring** — track fact-checks mentioning a company or product - **Election integrity** — assemble a feed of newly reviewed political claims by date ### How to use 1. Add your topics, names, or claim phrasings to **Queries** — one per line. 2. (Optional) Restrict by **Language code** (e.g. `en`, `es`, `pt`). 3. (Optional) Filter to a single fact-checker via **Publisher site filter** (e.g. `snopes.com`, `politifact.com`). 4. (Optional) Limit by **Max age (days)** to focus on recent reviews. 5. Set **Max results per query** (default 50, max 500). The actor paginates 10 at a time. 6. Run — each reviewed claim becomes its own dataset row. ### Output schema | Field | Type | Description | |---|---|---| | `query` | string | The input query | | `rank` | number | 1-based rank within the query (0 if no results/error) | | `status` | string | `success`, `no-results`, or `error` | | `claimText` | string \| null | The claim being fact-checked | | `claimant` | string \| null | Who said it (politician, public figure, social-media account) | | `claimDate` | string \| null | When the claim was made (ISO timestamp) | | `reviewPublisherName` | string \| null | Fact-checker name | | `reviewPublisherSite` | string \| null | Fact-checker domain | | `reviewUrl` | string \| null | URL of the published fact-check | | `reviewTitle` | string \| null | Title of the fact-check article | | `reviewDate` | string \| null | When the fact-check was published (ISO timestamp) | | `textualRating` | string \| null | The verdict in the publisher's own words ("False", "Pants on Fire", "Mostly True", …) | | `languageCode` | string \| null | Language of the review | | `error` | string \| null | Error message if `status` is `error` | If a claim has multiple reviews (e.g. reviewed by both Snopes and PolitiFact), each review is its own row — same claim text, different publisher/rating/URL. ### Tips - **Phrase queries broadly** — search "vaccine" rather than a specific debunked claim; the API matches across claim text and review text. - **Ratings are not normalised** — `textualRating` is whatever the publisher wrote. Map them to your own scale downstream. - **Coverage skews English** and US-centric, but the API supports many languages — try Spanish or Portuguese for Latin-American coverage. - Use **Publisher site filter** to build a single-publisher feed for a daily digest. - Some claims have a `claimDate` years before the `reviewDate` — useful to spot resurfaced misinformation. # Actor input Schema ## `queries` (type: `array`): Topics, names, or claims to search for fact checks. ## `languageCode` (type: `string`): BCP-47 language code to restrict results, e.g. en, es, fr. Leave empty for all languages. ## `reviewPublisherSiteFilter` (type: `string`): Restrict to a single publisher domain (e.g. snopes.com, politifact.com, factcheck.org). Leave empty for all publishers. ## `maxAgeDays` (type: `integer`): Restrict to claims reviewed within the last N days. Leave empty for no time restriction. ## `maxResultsPerQuery` (type: `integer`): Maximum claim reviews returned per query. The actor auto-paginates in batches of 10. ## Actor input object example ```json { "queries": [ "climate change", "vaccine" ], "languageCode": "en", "maxResultsPerQuery": 50 } ```` # Actor output Schema ## `results` (type: `string`): One record per claim review: query, rank, status, claimText, claimant, claimDate, reviewPublisherName, reviewPublisherSite, reviewUrl, reviewTitle, reviewDate, textualRating, languageCode. # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "queries": [ "climate change", "vaccine" ] }; // Run the Actor and wait for it to finish const run = await client.actor("seemuapps/google-fact-check-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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "queries": [ "climate change", "vaccine", ] } # Run the Actor and wait for it to finish run = client.actor("seemuapps/google-fact-check-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 '{ "queries": [ "climate change", "vaccine" ] }' | apify call seemuapps/google-fact-check-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=seemuapps/google-fact-check-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Fact Check Scraper", "description": "Search Google's Fact Check Tools database for claims and their reviews publisher, rating, source URL and export them to a clean dataset.", "version": "1.0", "x-build-id": "qDP9XZSfQQ19qKPWc" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/seemuapps~google-fact-check-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-seemuapps-google-fact-check-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/seemuapps~google-fact-check-scraper/runs": { "post": { "operationId": "runs-sync-seemuapps-google-fact-check-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/seemuapps~google-fact-check-scraper/run-sync": { "post": { "operationId": "run-sync-seemuapps-google-fact-check-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "queries" ], "properties": { "queries": { "title": "Queries", "type": "array", "description": "Topics, names, or claims to search for fact checks.", "items": { "type": "string" } }, "languageCode": { "title": "Language code", "type": "string", "description": "BCP-47 language code to restrict results, e.g. en, es, fr. Leave empty for all languages.", "default": "en" }, "reviewPublisherSiteFilter": { "title": "Publisher site filter", "type": "string", "description": "Restrict to a single publisher domain (e.g. snopes.com, politifact.com, factcheck.org). Leave empty for all publishers." }, "maxAgeDays": { "title": "Max age (days)", "minimum": 1, "type": "integer", "description": "Restrict to claims reviewed within the last N days. Leave empty for no time restriction." }, "maxResultsPerQuery": { "title": "Max results per query", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum claim reviews returned per query. The actor auto-paginates in batches of 10.", "default": 50 } } }, "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 } } } } } } } } } } ```