# StockTwits 爬蟲｜美股社群輿情、情緒、熱門標的一鍵匯出（免 API） (`claude_code_reviewer/stocktwits-scraper`) Actor 抓 StockTwits 美股社群：symbol 模式抓個股貼文（多空情緒），trending 模式抓熱門標的榜（含加密貨幣），輸出 JSON／CSV／Excel。美股輿情、情緒指標、量化訊號必備。 - **URL**: https://apify.com/claude\_code\_reviewer/stocktwits-scraper.md - **Developed by:** [Chad](https://apify.com/claude_code_reviewer) (community) - **Categories:** News, Lead generation, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 社群訊息 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 ## StockTwits 爬蟲｜美股社群輿情、熱門標的一鍵下載（免 API、免登入） 一個 Actor 搞定 StockTwits 兩種你會用到的抓取模式：**個股討論串**（依股票代號拿社群貼文、bullish/bearish 情緒標籤、用戶資訊）與**熱門標的榜**（拿當下最多人討論的股票與加密幣排行）。不需要登入、不需要 API token、批量貼上股票代號都吃得下。全程走 StockTwits 公開 JSON API，不開瀏覽器，速度快、成本低。 給誰用的：量化研究員、meme-stock 監控工程師、情緒因子開發者、財經 side project 作者、學術論文需要社群情緒資料集的研究者。 --- ### 能抓到什麼 #### symbol 模式 — 個股貼文 每一則討論都會拿到下面這些欄位（缺值一律回 `null`，不會少欄位）： | 欄位 | 說明 | 範例 | | -------------------- | -------------------------------------- | --------------------------------------------------------- | | `message_id` | 貼文 ID | `654321` | | `symbol` | 查詢時指定的股票代號 | `AAPL` | | `symbols_mentioned` | 貼文中提到的所有標的代號 | `["AAPL", "MSFT"]` | | `body` | 貼文內容 | `$AAPL breaking out of the wedge 🚀` | | `sentiment` | 情緒標籤 | `Bullish`、`Bearish`、`null`（未標記） | | `user_id` | 用戶 ID | `987654` | | `username` | 用戶名 | `trader_joe` | | `user_followers` | 粉絲數 | `1205` | | `likes_count` | 讚數 | `42` | | `source_app` | 發文用的應用程式 | `StockTwits Web` | | `message_created_at` | 發文時間（ISO 8601） | `2026-07-04T08:23:11.000Z` | | `message_url` | 貼文網址 | `https://stocktwits.com/trader_joe/message/654321` | | `source_mode` | 來源模式 | `symbol` | | `source_query` | 查詢時用的股票代號 | `AAPL` | | `scraped_at` | 抓取當下時間（ISO 8601） | `2026-07-04T08:30:00.000Z` | #### trending 模式 — 熱門標的榜 | 欄位 | 說明 | 範例 | | ----------------- | -------------------------------- | --------------------------- | | `symbol` | 股票/加密幣代號 | `NVDA` | | `symbol_title` | 標的全名 | `NVIDIA Corp.` | | `exchange` | 上市交易所 | `NASDAQ` | | `watchlist_count` | 追蹤人數 | `348721` | | `instrument_class`| 標的類型 | `Equity`、`Cryptocurrency` | | `trending_score` | 熱度分數（相對值） | `0.842` | | `source_mode` | 來源模式 | `trending` | | `source_query` | 查詢條件（固定值） | `trending` | | `scraped_at` | 抓取當下時間（ISO 8601） | `2026-07-04T08:30:00.000Z` | --- ### 兩種模式一個爬蟲 | 模式 | 幹嘛用的 | 計費事件 | 單價 | | ------------------ | --------------------------------------------------------- | ----------------------------- | ------ | | 📈 **symbol** | 依股票代號抓個股討論串（含 bullish/bearish 情緒標籤） | `search-listing`（每則貼文） | $0.002 | | 🔥 **trending** | 抓 StockTwits 當下熱門標的清單（股票＋加密幣混合） | `search-listing`（每個標的） | $0.002 | 不管跑哪個模式，每次 Run 啟動都會額外收一次性的 `actor-start` 費用 **$0.005**。所有計費都在資料成功寫入 dataset **之後**才會收，Run 結束時 log 會印出 `total_items / charged / skipped` 讓你對帳。 --- ### 輸入欄位 | 欄位 | 型別 | 必填 | 預設 | 說明 | | -------------------- | -------- | :------------------: | :---------: | ---------------------------------------------------------------------------------------------------------------------------------------------------------- | | `mode` | enum | 建議填 | 自動偵測 | `symbol`（個股討論串）/ `trending`（熱門標的榜）擇一。留空時若有填 symbols 自動切 symbol 模式，否則切 trending 模式。 | | `symbols` | string[] | `symbol` 模式必填 | — | 股票代號，例如 `AAPL`、`TSLA`、`NVDA`。大小寫不限，自動轉大寫。單次最多 **100** 個。 | | `bulkInput` | string | 選填 | — | **一行一個股票代號**，按 Enter 換行，不要加引號或逗號。執行時自動併入 symbols 欄位。從 Google Sheet / Excel 複製一整欄貼進來最快。trending 模式此欄位無效。 | | `maxItems` | integer | 選填 | `50` | 每個股票代號（symbol 模式）或整個 trending 榜最多回傳幾筆（1-500）。 | | `proxyConfiguration` | object | 選填 | 不用 proxy | 預設直連，通常不用設定。大量抓取遇到 429 才建議開啟 Apify Proxy。 | --- ### 範例 **📈 抓多檔個股討論串** ```json { "mode": "symbol", "symbols": ["AAPL", "TSLA", "NVDA"], "maxItems": 30 } ```` **📋 批量貼入股票代號（bulkInput）** ```json { "mode": "symbol", "bulkInput": "AAPL\nTSLA\nNVDA\nAMD\nMSFT", "maxItems": 20 } ``` **🔥 抓熱門標的榜（trending）** ```json { "mode": "trending", "maxItems": 50 } ``` *** ### 計費說明 每次 Run 固定收 `actor-start`（$0.005）一次。此後每筆成功寫入 dataset 的資料收 `search-listing`（$0.002）——不管是 symbol 模式的個別貼文還是 trending 模式的標的都是同一單價。抓 50 筆的最低費用：$0.005 + 50 × $0.002 = **$0.105**。Run 結束時 log 印出 `total_items / charged / skipped`，可直接對帳。 *** ### 幾個要注意的地方 - **只抓公開資料**。不需要登入、不需要 StockTwits 帳號，也不會存取任何需要驗證才看得到的內容。 - **免 API token**。填好 input 就能跑，沒有任何金鑰要設定。 - **trending 模式不用填 symbols**。直接把 `mode` 設為 `trending`、填 `maxItems` 就好，symbols 欄位留空即可。 - **symbols 大小寫不限**。填 `aapl` 跟 `AAPL` 結果一樣，程式自動轉大寫並去重複。 - **對 StockTwits 伺服器友善**。每個 domain 併發數 ≤5，遇到失敗會用指數退避重試最多 3 次。連續 5 頁拿不到新資料就會自己停並在 log 寫原因，不會空轉燒錢。 - **sentiment 欄位可能為 null**。StockTwits 情緒標籤是用戶自行選填，大部分貼文不會標記，`null` 是正常值。 - **同一則貼文若一次 Run 中被重複爬到，會去重複只保留一筆**（依 `message_id` 去重）。 *** ### 常見問題 **Q: trending 模式會抓到加密幣嗎？** 會。StockTwits trending 榜混合股票與加密幣，可以用 `instrument_class` 欄位（`Equity` vs `Cryptocurrency`）區分。 **Q: symbol 模式翻頁怎麼停？** 兩個條件任一滿足就停：(1) 已達 `maxItems`；(2) 連續 5 頁都沒有新貼文（stale 停止）。 **Q: 費用怎麼算？** 每次 Run 啟動收 `actor-start`（$0.005）；之後每筆資料收 `search-listing`（$0.002）。資料成功寫入 dataset 後才收費，Run log 印出實際收費筆數。 **Q: 抓不到資料怎麼辦？** 先確認股票代號有無打錯（StockTwits 只支援有在平台上出現過的代號），或直接切 trending 模式確認服務正常。若連 trending 也空回應，可能是 StockTwits 短暫限流，等一會兒再試。 **Q: 能抓情緒統計（多空比）嗎？** v1.0 只回原始貼文資料，多空比統計（sentiment aggregation）規劃在 v1.1 加入。你可以自行用 Python/Excel 對 `sentiment` 欄位做統計。 *** ### 部署 ```bash apify login # 首次：貼上 Apify token（不會寫進 repo） apify push # 建置並上傳到 Apify Store ``` 上架後在 Apify Console 的 Monetization 設定 PPE 事件單價： `actor-start` $0.005、`search-listing` $0.002。 *** ### 免責聲明 本爬蟲只收集 StockTwits **公開可見**的社群資料，資料僅供研究與個人用途使用，不用於任何未經授權的商業轉售。使用前請自行確認符合 StockTwits 服務條款與當地法規。對於資料的正確性、即時性或完整性，本 Actor 不做任何保證，投資決策請以正規財務資訊管道為準，本 Actor 產出的社群輿情資料不構成任何投資建議。 *** *StockTwits 爬蟲、stocktwits API、美股輿情、社群情緒、bullish bearish、meme stock 監控、trending stocks、加密幣討論、量化因子、選股輿情* # Actor input Schema ## `mode` (type: `string`): 要抓什麼？留空時，若有填 symbols 就自動切 symbol 模式，否則切 trending 模式。 ## `symbols` (type: `array`): symbol 模式的股票代號，例如：AAPL、TSLA、NVDA。一次最多 100 個。大小寫不限，自動轉大寫。 ## `bulkInput` (type: `string`): **一行一個股票代號**，按 Enter 換行，不要加引號或逗號。執行時自動併入 symbols 欄位。從 Google Sheet / Excel 複製一整欄貼進來最快。trending 模式此欄位無效。 ## `maxItems` (type: `integer`): 每個股票代號（symbol 模式）或整個 trending 榜最多回傳幾筆。越多費用越高。 ## `proxyConfiguration` (type: `object`): StockTwits 公開 API 對 datacenter 請求友善，預設不用 proxy 即可運作。只有大量抓取遇到被擋（429）時才建議開啟。 ## Actor input object example ```json { "symbols": [ "AAPL", "TSLA" ], "maxItems": 50, "proxyConfiguration": { "useApifyProxy": false } } ``` # Actor output Schema ## `dataset` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "symbols": [ "AAPL", "TSLA" ] }; // Run the Actor and wait for it to finish const run = await client.actor("claude_code_reviewer/stocktwits-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "symbols": [ "AAPL", "TSLA", ] } # Run the Actor and wait for it to finish run = client.actor("claude_code_reviewer/stocktwits-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 '{ "symbols": [ "AAPL", "TSLA" ] }' | apify call claude_code_reviewer/stocktwits-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=claude_code_reviewer/stocktwits-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "StockTwits 爬蟲｜美股社群輿情、情緒、熱門標的一鍵匯出（免 API）", "description": "抓 StockTwits 美股社群：symbol 模式抓個股貼文（多空情緒），trending 模式抓熱門標的榜（含加密貨幣），輸出 JSON／CSV／Excel。美股輿情、情緒指標、量化訊號必備。", "version": "1.0", "x-build-id": "TjymFYv3EwKiMHlSC" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/claude_code_reviewer~stocktwits-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-claude_code_reviewer-stocktwits-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/claude_code_reviewer~stocktwits-scraper/runs": { "post": { "operationId": "runs-sync-claude_code_reviewer-stocktwits-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/claude_code_reviewer~stocktwits-scraper/run-sync": { "post": { "operationId": "run-sync-claude_code_reviewer-stocktwits-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "mode": { "title": "🎯 模式", "enum": [ "symbol", "trending" ], "type": "string", "description": "要抓什麼？留空時，若有填 symbols 就自動切 symbol 模式，否則切 trending 模式。" }, "symbols": { "title": "📈 股票代號", "maxItems": 100, "uniqueItems": true, "type": "array", "description": "symbol 模式的股票代號，例如：AAPL、TSLA、NVDA。一次最多 100 個。大小寫不限，自動轉大寫。", "items": { "type": "string" } }, "bulkInput": { "title": "📋 批量貼上", "type": "string", "description": "**一行一個股票代號**，按 Enter 換行，不要加引號或逗號。執行時自動併入 symbols 欄位。從 Google Sheet / Excel 複製一整欄貼進來最快。trending 模式此欄位無效。" }, "maxItems": { "title": "📊 最多抓幾筆", "minimum": 1, "maximum": 500, "type": "integer", "description": "每個股票代號（symbol 模式）或整個 trending 榜最多回傳幾筆。越多費用越高。", "default": 50 }, "proxyConfiguration": { "title": "🌐 Proxy（進階，通常不用開）", "type": "object", "description": "StockTwits 公開 API 對 datacenter 請求友善，預設不用 proxy 即可運作。只有大量抓取遇到被擋（429）時才建議開啟。", "default": { "useApifyProxy": false } } } }, "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 } } } } } } } } } } ```