# X/Twitter search Tweets scrapper (`simoit/x-twitter-search-tweets-scrapper`) Actor Collect tweets for any topic and filter them to keep only useful, analysis-ready results. - **URL**: https://apify.com/simoit/x-twitter-search-tweets-scrapper.md - **Developed by:** [simoit](https://apify.com/simoit) (community) - **Categories:** Lead generation, Social media - **Stats:** 4 total users, 2 monthly users, 50.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing $0.30 / 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. 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 ## Tweet Scraper ![SIMO IT logo](https://simoit.tech/favicon.ico) Collect tweets for any topic and narrow the results with query, author, date, engagement, and media filters to keep the output analysis-ready. ### About SIMO IT SIMO IT delivers practical scraping and automation tools that help teams extract value from social platforms faster. ### Features - find tweets by keyword or query phrase - collect by conversation IDs (`conversation_id:`) - collect tweets directly from selected handles - narrow results to specific authors, recipients, or mentions - limit data to a selected date range - filter for stronger engagement signals - focus on media type (image/video) - paginate through larger result sets for deeper analysis ### Use cases - brand and campaign monitoring - sentiment and reaction analysis - market research for content and sales teams - building datasets for AI and classification pipelines ### Output A clean list of matching tweets, ready for reporting, analytics, and downstream automation. ### How to use 1. Open the Actor on Apify. 2. Provide `searchTerms`, `conversationIds`, or `startUrls`. 3. Add optional filters and pagination based on your use case. 4. Run the Actor and use the dataset output in Apify. No technical setup is required from your side. Backend infrastructure is managed by SIMO IT. Need a custom plan, custom limits, or a tailored data workflow? Contact `contact@simoit.tech`. ### Related Actors - Need tweets from one specific profile instead of broad search results? Use [Profile Scraper](https://apify.com/simoit/x-twitter-profile-scrapper). - Need account metadata, followers, or following instead of tweets? Use [User Scraper](https://apify.com/simoit/x-twitter-user-scrapper). - Need posts from a curated X list? Use [List Scraper](https://apify.com/simoit/x-twitter-list-scraper). - Need preset or country-level trend feeds before drilling into tweets? Use [Trends Scraper](https://apify.com/simoit/x-twitter-preset-trends-scrapper) or [Global Trending Scraper](https://apify.com/simoit/x-twitter-trends-scrapper). ### Input - `searchTerms` (string, optional): Main search phrase (or multiple comma/newline terms). - `conversationIds` (string, optional): Conversation IDs (comma/newline), internally converted to `conversation_id:`. - `startUrls` (string, optional): X/Twitter search URLs (`x.com` / `twitter.com`), comma-separated or new lines. - `sort` (string, optional, default: `latest`): `latest` or `top`. - `fromUsers` (string, optional): Comma-separated usernames for `from:` filter. - `toUsers` (string, optional): Comma-separated usernames for `to:` filter. - `mentioningUsers` (string, optional): Comma-separated usernames to be mentioned. - `startDate` (string, optional): Start date in `YYYY-MM-DD`. - `endDate` (string, optional): End date in `YYYY-MM-DD`. - `minimumLikes` (integer, optional): Minimum likes threshold. - `minimumRetweets` (integer, optional): Minimum retweets threshold. - `minimumReplies` (integer, optional): Minimum replies threshold. - `onlyImage` (boolean, optional, default: `false`): Return only image tweets. - `onlyVideo` (boolean, optional, default: `false`): Return only video tweets. - `onlyVerifiedUsers` (boolean, optional, default: `false`): Return only verified-account tweets. - `includeReplies` (boolean, optional, default: `true`): Include replies. - `includeRetweets` (boolean, optional, default: `true`): Include retweets. - `withinRadius` (string, optional): Geo filter, format: `lat,lon,radius` (for example `52.23,21.01,10km`). - `page` (integer, optional, default: `1`): Starting page number. - `limit` (integer, optional, default: `20`, max: `100`): Records per page. - `maxPages` (integer, optional, default: `1`): Maximum number of pages to fetch. - `maxItems` (integer, optional): Hard cap for total output records. Legacy compatibility: - The Actor still accepts aliases such as `author`, `inReplyTo`, `mentioning`, `start`, `end`, `since`, `until`, and `minimumFavorites`. - Those aliases are supported for backward compatibility, but they are intentionally not exposed in the public input UI. #### Filters and pagination - search target: `searchTerms`, `conversationIds`, `startUrls` - author/mention filters: `fromUsers`/`author`, `toUsers`/`inReplyTo`, `mentioningUsers`/`mentioning` - date filters: `startDate`/`start`/`since`, `endDate`/`end`/`until` - quality filters: `minimumLikes`/`minimumFavorites`, `minimumRetweets`, `minimumReplies` - media/account filters: `onlyImage`, `onlyVideo`, `onlyVerifiedUsers` - inclusion switches: `includeReplies`, `includeRetweets` - geo filter: `withinRadius` - page controls: `page`, `limit`, `maxPages`, `maxItems` #### Example input ```json { "searchTerms": "open source ai agents", "conversationIds": "1891042203344556600", "sort": "latest", "fromUsers": "openai,apify", "startDate": "2026-02-01", "endDate": "2026-02-20", "minimumLikes": 10, "includeReplies": true, "onlyVideo": false, "maxItems": 50 } ```` #### Example output ```json { "id": 1891042203344556600, "id_str": "1891042203344556600", "url": "https://x.com/openai/status/1891042203344556600", "date": "2026-02-20T08:30:00+00:00", "lang": "en", "rawContent": "We shipped a new update today.", "replyCount": 42, "retweetCount": 310, "likeCount": 1520, "quoteCount": 18, "bookmarkedCount": 0, "conversationId": 1891042203344556600, "conversationIdStr": "1891042203344556600", "hashtags": ["AI", "OpenAI"], "cashtags": [], "mentionedUsers": [], "links": [], "viewCount": 120034, "user": { "id": 4398626122, "id_str": "4398626122", "url": "https://x.com/openai", "username": "openai", "displayname": "OpenAI", "followersCount": 5500000, "friendsCount": 12, "verified": true }, "media": { "photos": [], "videos": [], "animated": [] }, "_type": "snscrape.modules.twitter.Tweet" } ``` ### FAQ **Do I need my own backend or API setup?**\ No. This Actor is ready to run on Apify, and backend infrastructure is managed by SIMO IT. **Can I collect more than one page of results?**\ Yes. Use `page`, `limit`, and `maxPages` to control pagination. **Can I narrow results to high-quality tweets only?**\ Yes. Use engagement filters like `minimumLikes`, `minimumRetweets`, and `minimumReplies`. **Does this Actor support legacy alias fields?**\ Yes. It supports aliases like `author`, `inReplyTo`, `mentioning`, `start`/`end`, `since`/`until`, and `minimumFavorites`. # Actor input Schema ## `searchTerms` (type: `string`): Search phrase or multiple queries (comma/newline). ## `conversationIds` (type: `string`): Conversation IDs, comma-separated or new lines. Converted to conversation\_id: queries. ## `startUrls` (type: `string`): Optional X/Twitter search URLs (comma-separated or new lines). Search URLs infer query. ## `sort` (type: `string`): Result sorting mode. ## `fromUsers` (type: `string`): CSV usernames for from: filter. ## `toUsers` (type: `string`): CSV usernames for to: filter. ## `mentioningUsers` (type: `string`): CSV usernames that should be mentioned. ## `startDate` (type: `string`): Start date (YYYY-MM-DD). ## `endDate` (type: `string`): End date (YYYY-MM-DD). ## `minimumLikes` (type: `integer`): Minimum likes count. ## `minimumRetweets` (type: `integer`): Minimum retweets count. ## `minimumReplies` (type: `integer`): Minimum replies count. ## `onlyImage` (type: `boolean`): Only tweets with images. ## `onlyVideo` (type: `boolean`): Only tweets with videos. ## `onlyVerifiedUsers` (type: `boolean`): Only tweets from verified accounts. ## `includeReplies` (type: `boolean`): Include reply tweets. ## `includeRetweets` (type: `boolean`): Include retweets. ## `withinRadius` (type: `string`): Geocode in lat,lon,radius format (for example 52.23,21.01,10km). ## `page` (type: `integer`): Starting page number. ## `limit` (type: `integer`): Items per page. ## `maxPages` (type: `integer`): Maximum number of pages to fetch. ## `maxItems` (type: `integer`): Maximum number of output items to push. ## Actor input object example ```json { "searchTerms": "openai", "sort": "latest", "onlyImage": false, "onlyVideo": false, "onlyVerifiedUsers": false, "includeReplies": true, "includeRetweets": true, "page": 1, "limit": 10, "maxPages": 1, "maxItems": 10 } ``` # Actor output Schema ## `results` (type: `string`): No description ## `runReport` (type: `string`): No description ## `userErrorReport` (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 = { "searchTerms": "openai", "limit": 10, "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("simoit/x-twitter-search-tweets-scrapper").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 = { "searchTerms": "openai", "limit": 10, "maxItems": 10, } # Run the Actor and wait for it to finish run = client.actor("simoit/x-twitter-search-tweets-scrapper").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 '{ "searchTerms": "openai", "limit": 10, "maxItems": 10 }' | apify call simoit/x-twitter-search-tweets-scrapper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=simoit/x-twitter-search-tweets-scrapper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "X/Twitter search Tweets scrapper", "description": "Collect tweets for any topic and filter them to keep only useful, analysis-ready results.", "version": "0.0", "x-build-id": "SAE0cs7nae2xhk5Ip" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/simoit~x-twitter-search-tweets-scrapper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-simoit-x-twitter-search-tweets-scrapper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/simoit~x-twitter-search-tweets-scrapper/runs": { "post": { "operationId": "runs-sync-simoit-x-twitter-search-tweets-scrapper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/simoit~x-twitter-search-tweets-scrapper/run-sync": { "post": { "operationId": "run-sync-simoit-x-twitter-search-tweets-scrapper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "searchTerms": { "title": "Search terms", "type": "string", "description": "Search phrase or multiple queries (comma/newline)." }, "conversationIds": { "title": "Conversation IDs", "type": "string", "description": "Conversation IDs, comma-separated or new lines. Converted to conversation_id: queries." }, "startUrls": { "title": "Start URLs", "type": "string", "description": "Optional X/Twitter search URLs (comma-separated or new lines). Search URLs infer query." }, "sort": { "title": "Sort", "enum": [ "latest", "top" ], "type": "string", "description": "Result sorting mode.", "default": "latest" }, "fromUsers": { "title": "From users", "type": "string", "description": "CSV usernames for from: filter." }, "toUsers": { "title": "To users", "type": "string", "description": "CSV usernames for to: filter." }, "mentioningUsers": { "title": "Mentioning users", "type": "string", "description": "CSV usernames that should be mentioned." }, "startDate": { "title": "Start date", "type": "string", "description": "Start date (YYYY-MM-DD)." }, "endDate": { "title": "End date", "type": "string", "description": "End date (YYYY-MM-DD)." }, "minimumLikes": { "title": "Minimum likes", "minimum": 0, "type": "integer", "description": "Minimum likes count." }, "minimumRetweets": { "title": "Minimum retweets", "minimum": 0, "type": "integer", "description": "Minimum retweets count." }, "minimumReplies": { "title": "Minimum replies", "minimum": 0, "type": "integer", "description": "Minimum replies count." }, "onlyImage": { "title": "Only image", "type": "boolean", "description": "Only tweets with images.", "default": false }, "onlyVideo": { "title": "Only video", "type": "boolean", "description": "Only tweets with videos.", "default": false }, "onlyVerifiedUsers": { "title": "Only verified users", "type": "boolean", "description": "Only tweets from verified accounts.", "default": false }, "includeReplies": { "title": "Include replies", "type": "boolean", "description": "Include reply tweets.", "default": true }, "includeRetweets": { "title": "Include retweets", "type": "boolean", "description": "Include retweets.", "default": true }, "withinRadius": { "title": "Within radius", "type": "string", "description": "Geocode in lat,lon,radius format (for example 52.23,21.01,10km)." }, "page": { "title": "Page", "minimum": 1, "type": "integer", "description": "Starting page number.", "default": 1 }, "limit": { "title": "Limit", "minimum": 1, "maximum": 100, "type": "integer", "description": "Items per page.", "default": 20 }, "maxPages": { "title": "Max pages", "minimum": 1, "type": "integer", "description": "Maximum number of pages to fetch.", "default": 1 }, "maxItems": { "title": "Max items", "minimum": 1, "type": "integer", "description": "Maximum number of output items to push." } } }, "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 } } } } } } } } } } ```