# Twitter Hashtag Scraper (Pay Per Result) | 2024 | $0.5/1000 (`fastcrawler/twitter-hashtag-scraper-pay-per-result-2024-0-5-1000`) Actor [free twitter api](https://twitterxapi.com) Twitter Hashtag Scraper V2 is a powerful, pay-per-result tool for scraping Twitter (X). Perfect for tracking trends, monitoring mentions, or research, it delivers precise hashtag data efficiently. - **URL**: https://apify.com/fastcrawler/twitter-hashtag-scraper-pay-per-result-2024-0-5-1000.md - **Developed by:** [fastcrawler](https://apify.com/fastcrawler) (community) - **Categories:** AI, Social media, E-commerce - **Stats:** 18 total users, 18 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing $0.50 / 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. 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 Hashtag Scraper V2 (Pay Per Result) - X / Twitter Scraper | 2024 Get 1,000 results for just $0.5! Introducing the Twitter Hashtag Fast Scraper, your go-to solution for scraping Twitter hashtags. This powerful tool combines blazing-fast speed with advanced data extraction capabilities, making it perfect for social media analysts, marketers, and researchers. Unlock the power of hashtag analytics with Tweet Hashtag Scraper V2β€”a cutting-edge, pay-per-result solution for scraping Twitter (X). Whether you're tracking trending topics, monitoring brand mentions, or diving into data for research, this tool ensures precision and efficiency. With its streamlined approach, you only pay for the results you need, making it both cost-effective and performance-driven. Perfect for marketers, analysts, and developers seeking a reliable Twitter scraping solution. Discover insights, fuel strategies, and stay ahead of the curve with Tweet Hashtag Scraper V2β€”the ultimate tool for hashtag-based data collection! ### Input Parameters | Field | Type | Description | |----|----------|---------------| | Hashtag | string | a hashtag,like #trump | | Start Time | string | Specify the datetime (yyyy-MM-dd_HH:mm:ss_UTC),Returns tweets sent after the given date. | | End Time | string | Specify the datetime (yyyy-MM-dd_HH:mm:ss_UTC),Returns tweets sent before the given date. | | Sort By | string | Sorts search results by the given option. | | Maximum number of items on output | int | Maximum number of items that you want as output. | | Minimum retweets | int | Returns tweets with at least the given number of retweets. | | Minimum Likes | int | Returns tweets with at least the given number of Likes. | | Minimum Replies | int | Returns tweets with at least the given number of replies. | | Only verified users | int | If checked then returns tweets by users who are verified. | | Only Twitter Blue | int | If checked then returns tweets by users who are Twitter Blue subscribers. | | lang | string | lang,eg:en | ### Output Example { "type": "tweet", "id": 1847792268444328200, "viewCount": 412, "url": "https://x.com/CallBotCrypto/status/1847792268444328117", "text": "+4.2% predicted on #GLM! #LFG\n\nData-driven, AI-powered: Welcome to the next level of trading! πŸš€\n\n#golemproject\n#ape #SEC #pepe #wen #base #ADX\nhttps://t.co/VxphuDHFBT https://t.co/IWShA3IlJ5", "isQuote": true, "isRetweet": false, "retweetCount": 1, "replyCount": 0, "likeCount": 2, "quoteCount": 0, "createdAt": "2024-10-20 00:09:41+00:00", "lang": "en", "bookmarkCount": 0, "isReply": false, "source": "CallBot_Status", "author": { "type": "user", "username": "CallBotCrypto", "url": "https://x.com/CallBotCrypto", "id": 1506427976912720000, "name": "Better CallBot", "isVerified": false, "isBlueVerified": true, "verifiedType": null, "profilePicture": "https://pbs.twimg.com/profile_images/1724513165503827968/XiY3IPV9_normal.png", "coverPicture": "https://pbs.twimg.com/profile_banners/1506427976912719873/1699464515", "description": "πŸ‘‰ Performing continuous #AI-based analyses and sharing the results!\n\nWe love #blockchain and numbers – We make big data #crypto analyses accessible to everyone", "location": "", "followers": 6125, "following": 10, "protected": null, "createdAt": "2022-03-23 00:30:22+00:00", "favouritesCount": 11433, "mediaCount": 8364, "statusesCount": 26227, "listedCount": 34 }, "quote": { "type": "tweet", "id": 1847520225178092000, "text": "⚑ ⚑ ⚑ #GLM/USDT ⚑ ⚑ ⚑\n\nEnter at: 0.3439$ 🏹\nTake profit at: 0.3587$ πŸ’° 🎯\nStop loss: 0.3291$ β˜‚οΈ\nAccuracy: 79.5% πŸ› \n\nBringing you trading #signals. Remember to research!\n#golemproject\n#bullish #MATIC #nfts #GM #DIA", "retweetCount": 1, "replyCount": 1, "likeCount": 4, "quoteCount": 1, "createdAt": "2024-10-19 06:08:41+00:00", "lang": "en", "bookmarkCount": 0, "author": { "type": "user", "username": "CallBotCrypto", "url": "https://x.com/CallBotCrypto", "id": 1506427976912720000, "name": "Better CallBot", "isVerified": false, "isBlueVerified": true, "verifiedType": null, "profilePicture": "https://pbs.twimg.com/profile_images/1724513165503827968/XiY3IPV9_normal.png", "coverPicture": "https://pbs.twimg.com/profile_banners/1506427976912719873/1699464515", "description": "πŸ‘‰ Performing continuous #AI-based analyses and sharing the results!\n\nWe love #blockchain and numbers – We make big data #crypto analyses accessible to everyone", "location": "", "followers": 6125, "following": 10, "protected": null, "createdAt": "2022-03-23 00:30:22+00:00", "favouritesCount": 11433, "mediaCount": 8364, "statusesCount": 26227, "listedCount": 34 } }, "retweetedTweet": null, "media": "Media(photos=[MediaPhoto(url='https://pbs.twimg.com/media/GaStRaHXYAARE-7.jpg')], videos=[], animated=[])", "cashtags": [], "hashtags": [ "GLM", "LFG", "golemproject", "ape", "SEC", "pepe", "wen", "base", "ADX" ], "links": [ "TextLink(url='https://x.com/CallBotCrypto/status/1847520225178091977', text='x.com/CallBotCrypto/…', tcourl='https://t.co/VxphuDHFBT')" ], "conversationId": 1847792268444328200, "card": null, "coordinates": null, "mentionedUsers": [] } ### Contact and Feature Requests If you need any sort of support, please send an email to fastcrawler9@gmail.com or [contact us](https://t.me/FastScraperCustomerBot) # Actor input Schema ## `hashtag` (type: `string`): A hashtag ,like #btc ## `startTime` (type: `string`): Specify the datetime (yyyy-MM-dd_HH:mm:ss_UTC),Returns tweets sent after the given date. ## `endTime` (type: `string`): Specify the datetime (yyyy-MM-dd_HH:mm:ss_UTC),Returns tweets sent before the given date. ## `sortBy` (type: `string`): Sorts search results by the given option. ## `maxItems` (type: `integer`): Maximum number of items that you want as output. ## `minRetweets` (type: `integer`): Returns tweets with at least the given number of retweets. ## `minLikes` (type: `integer`): Returns tweets with at least the given number of Likes. ## `minReplies` (type: `integer`): Returns tweets with at least the given number of replies. ## `lang` (type: `string`): lang ## `onlyVerifiedUsers` (type: `boolean`): If checked then returns tweets by users who are verified. ## `onlyBuleVerifiedUsers` (type: `boolean`): If checked then returns tweets by users who are Twitter Blue subscribers. ## Actor input object example ```json { "hashtag": "btc", "startTime": "2024-12-07_00:00:00_UTC", "endTime": "2024-12-08_23:59:59_UTC", "sortBy": "Latest", "maxItems": 100, "minRetweets": 0, "minLikes": 0, "minReplies": 0 } ```` # 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 = { "hashtag": "btc", "startTime": "2024-12-07_00:00:00_UTC", "endTime": "2024-12-08_23:59:59_UTC", "sortBy": "Latest", "onlyVerifiedUsers": false, "onlyBuleVerifiedUsers": false }; // Run the Actor and wait for it to finish const run = await client.actor("fastcrawler/twitter-hashtag-scraper-pay-per-result-2024-0-5-1000").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = { "hashtag": "btc", "startTime": "2024-12-07_00:00:00_UTC", "endTime": "2024-12-08_23:59:59_UTC", "sortBy": "Latest", "onlyVerifiedUsers": False, "onlyBuleVerifiedUsers": False, } # Run the Actor and wait for it to finish run = client.actor("fastcrawler/twitter-hashtag-scraper-pay-per-result-2024-0-5-1000").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "hashtag": "btc", "startTime": "2024-12-07_00:00:00_UTC", "endTime": "2024-12-08_23:59:59_UTC", "sortBy": "Latest", "onlyVerifiedUsers": false, "onlyBuleVerifiedUsers": false }' | apify call fastcrawler/twitter-hashtag-scraper-pay-per-result-2024-0-5-1000 --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=fastcrawler/twitter-hashtag-scraper-pay-per-result-2024-0-5-1000", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Twitter Hashtag Scraper (Pay Per Result) | 2024 | $0.5/1000", "description": "[free twitter api](https://twitterxapi.com) Twitter Hashtag Scraper V2 is a powerful, pay-per-result tool for scraping Twitter (X). Perfect for tracking trends, monitoring mentions, or research, it delivers precise hashtag data efficiently.", "version": "0.0", "x-build-id": "CfvXWVB0wPcg27VAJ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/fastcrawler~twitter-hashtag-scraper-pay-per-result-2024-0-5-1000/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-fastcrawler-twitter-hashtag-scraper-pay-per-result-2024-0-5-1000", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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-hashtag-scraper-pay-per-result-2024-0-5-1000/runs": { "post": { "operationId": "runs-sync-fastcrawler-twitter-hashtag-scraper-pay-per-result-2024-0-5-1000", "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-hashtag-scraper-pay-per-result-2024-0-5-1000/run-sync": { "post": { "operationId": "run-sync-fastcrawler-twitter-hashtag-scraper-pay-per-result-2024-0-5-1000", "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": [ "hashtag" ], "properties": { "hashtag": { "title": "Hashtag", "type": "string", "description": "A hashtag ,like #btc " }, "startTime": { "title": "Start Time", "type": "string", "description": "Specify the datetime (yyyy-MM-dd_HH:mm:ss_UTC),Returns tweets sent after the given date." }, "endTime": { "title": "End Time", "type": "string", "description": "Specify the datetime (yyyy-MM-dd_HH:mm:ss_UTC),Returns tweets sent before the given date." }, "sortBy": { "title": "Sort By", "enum": [ "Top", "Latest" ], "type": "string", "description": "Sorts search results by the given option. ", "default": "Latest" }, "maxItems": { "title": "Maximum number of items on output", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of items that you want as output.", "default": 100 }, "minRetweets": { "title": "Minimum retweets", "minimum": 0, "maximum": 10000000, "type": "integer", "description": "Returns tweets with at least the given number of retweets.", "default": 0 }, "minLikes": { "title": "Minimum Likes", "minimum": 0, "maximum": 10000000, "type": "integer", "description": "Returns tweets with at least the given number of Likes.", "default": 0 }, "minReplies": { "title": "Minimum Replies", "minimum": 0, "maximum": 10000000, "type": "integer", "description": "Returns tweets with at least the given number of replies.", "default": 0 }, "lang": { "title": "lang", "enum": [ "am", "ar", "bg", "bn", "bo", "ca", "ch", "cs", "da", "de", "dv", "el", "en", "es", "et", "fa", "fi", "fr", "gu", "hi", "ht", "hu", "hy", "in", "is", "it", "iu", "iw", "ja", "ka", "km", "kn", "ko", "lo", "lt", "lv", "ml", "my", "ne", "nl", "no", "or", "pa", "pl", "pt", "ro", "ru", "si", "sk", "sl", "sv", "ta", "te", "th", "tl", "tr", "uk", "ur", "vi", "zh" ], "type": "string", "description": "lang" }, "onlyVerifiedUsers": { "title": "Only verified users", "type": "boolean", "description": "If checked then returns tweets by users who are verified." }, "onlyBuleVerifiedUsers": { "title": "Only Twitter Blue", "type": "boolean", "description": "If checked then returns tweets by users who are Twitter Blue subscribers." } } }, "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 } } } } } } } } } } ```