# Twitter / X Ad & Partnership API (`fastcrawler/twitter-x-ad-partnership-api`) Actor Extract paid partnership and sponsored post data from X (Twitter). This scraper analyzes tweet metadata to detect official 'Paid Partnership' labels and commercial relationships. Export results in structured JSON/CSV for compliance and influencer marketing analysis. - **URL**: https://apify.com/fastcrawler/twitter-x-ad-partnership-api.md - **Developed by:** [fastcrawler](https://apify.com/fastcrawler) (community) - **Categories:** Social media, AI, Agents - **Stats:** 4 total users, 2 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 paidresults This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## Twitter (X) Paid Partnership Scraper & Extractor A specialized, high-performance scraper designed to accurately detect and extract paid partnerships, sponsored content, and commercial advertisements from X (Twitter). By analyzing deep tweet metadata and standard JSON objects, this tool reveals the commercial relationships that standard APIs often miss. ### 🚀 Key Features - **Deep Metadata Extraction**: Bypasses the surface UI to detect official `Paid Partnership` labels and hidden `affiliate_label` flags within the tweet's raw data. - **Sponsorship Verification**: Identifies `promoted_content` attributes and invisible commercial relationship tags. - **Semantic Content Analysis**: Scans tweet text for compliance keywords and mandatory FTC disclosures (e.g., `#ad`, `#sponsored`, `#brandpartner`, `#promo`). - **Brand & Sponsor Intelligence**: Automatically extracts available details about the linked brand account or affiliate sponsor involved in the collaboration. - **High-Speed Batch Processing**: Concurrently process multiple tweet URLs or IDs in a single run, optimized for Apify's infrastructure. - **Developer-Ready JSON Export**: Provides clean, structured data ready for seamless integration into compliance dashboards, marketing analytics tools, or brand safety pipelines. ### 🎯 Ideal Use Cases - **Brand Compliance Audits**: Ensure influencers and KOLs are strictly adhering to FTC guidelines and correctly disclosing paid collaborations. - **Influencer Marketing Monitoring**: Automatically verify, track, and archive sponsored posts for your marketing campaigns at scale. - **Competitive Ad Intelligence**: Reverse-engineer competitor advertising strategies by discovering who they are sponsoring and how they label their partnerships. - **Market & Niche Research**: Analyze the saturation and performance of sponsored content within specific industries or targeted hashtags. ### 📥 Input Configuration The Actor accepts either raw Tweet IDs or full URLs. | Field | Type | Description | | :--- | :--- | :--- | | **tweetIds** | Array | List of target tweet IDs to analyze. | | **tweetUrls** | Array | (Optional) List of full X/Twitter URLs to analyze. | ### 📤 Output Structure The scraper returns a rich, structured JSON dataset for each processed tweet. *(Here is a sample output demonstrating the extracted metadata)*: ```json [ { "tweet_id": "2043777708430414218", "url": "[https://x.com/username/status/2043777708430414218](https://x.com/username/status/2043777708430414218)", "is_paid_promotion": false, "has_disclosure_keywords": false, "sponsor_details": null }, { "tweet_id": "2034246147318202855", "url": "[https://x.com/username/status/2034246147318202855](https://x.com/username/status/2034246147318202855)", "is_paid_promotion": true, "has_disclosure_keywords": true, "detected_keywords": ["#ad", "partner"], "sponsor_details": { "brand_name": "ExampleBrand", "brand_handle": "@ExampleBrand" } } ] ```` ### 💡 Support & Feedback If you need custom features, higher rate limits, or encounter any issues, please feel free to open an issue in the **Issues** tab. # Actor input Schema ## `tweetIds` (type: `array`): The id of the tweet to check paid partnership. Up to 10 items ## Actor input object example ```json { "tweetIds": [ "2043777708430414218" ] } ``` # Actor output Schema ## `overview` (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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "tweetIds": [ "2043777708430414218" ] }; // Run the Actor and wait for it to finish const run = await client.actor("fastcrawler/twitter-x-ad-partnership-api").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 = { "tweetIds": ["2043777708430414218"] } # Run the Actor and wait for it to finish run = client.actor("fastcrawler/twitter-x-ad-partnership-api").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 '{ "tweetIds": [ "2043777708430414218" ] }' | apify call fastcrawler/twitter-x-ad-partnership-api --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=fastcrawler/twitter-x-ad-partnership-api", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Twitter / X Ad & Partnership API", "description": "Extract paid partnership and sponsored post data from X (Twitter). This scraper analyzes tweet metadata to detect official 'Paid Partnership' labels and commercial relationships. Export results in structured JSON/CSV for compliance and influencer marketing analysis.", "version": "0.0", "x-build-id": "Oiif65K0GcTrFFNzi" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/fastcrawler~twitter-x-ad-partnership-api/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-fastcrawler-twitter-x-ad-partnership-api", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/fastcrawler~twitter-x-ad-partnership-api/runs": { "post": { "operationId": "runs-sync-fastcrawler-twitter-x-ad-partnership-api", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/fastcrawler~twitter-x-ad-partnership-api/run-sync": { "post": { "operationId": "run-sync-fastcrawler-twitter-x-ad-partnership-api", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "tweetIds" ], "properties": { "tweetIds": { "title": "tweetIds (Up to 10 items)", "type": "array", "description": "The id of the tweet to check paid partnership. Up to 10 items", "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```