# Stocktwits Trending Symbols Scraper (`parseforge/stocktwits-trending-symbols-scraper`) Actor Pull trending tickers from the Stocktwits public feed with symbol, watchlist\_count, message\_count, sentiment, last\_price, and change. Optionally filter by tickers like AAPL or TSLA. Useful for retail sentiment tracking, momentum screening, and meme stock research. - **URL**: https://apify.com/parseforge/stocktwits-trending-symbols-scraper.md - **Developed by:** [ParseForge](https://apify.com/parseforge) (community) - **Categories:** Automation, Integrations, Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $7.50 / 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. 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 ![ParseForge Banner](https://github.com/ParseForge/apify-assets/blob/ad35ccc13ddd068b9d6cba33f323962e39aed5b2/banner.jpg?raw=true) ## ๐Ÿ’ฌ Stocktwits Trending Symbols Scraper > ๐Ÿš€ **Export Stocktwits trending tickers in seconds, including watchlist count, message volume, sentiment skew, last price and change, straight from the public api.stocktwits.com trending stream.** > ๐Ÿ•’ **Last updated:** 2026-05-29 ยท **๐Ÿ“Š 11 fields** per record ยท Real-time retail sentiment ยท Auto-aggregated bullish/bearish skew The Stocktwits Trending Symbols Scraper turns the public Stocktwits trending message stream into a ticker-level sentiment dataset. It walks the most recent trending messages, aggregates how many bullish vs bearish posts each symbol got, and emits one row per ticker. | ๐ŸŽฏ Target Audience | ๐Ÿ’ก Primary Use Cases | |---|---| | ๐Ÿ“Š Retail flow analysts | Detect meme-stock momentum | | ๐Ÿ’ฑ Quant teams | Sentiment-as-a-feature backtests | | ๐Ÿข Hedge funds | Crowded-position risk monitoring | | ๐Ÿค– ML researchers | NLP-sentiment training labels | | ๐Ÿ“ฐ Financial journalists | Track retail mood shifts | | ๐Ÿ‘ฉโ€๐Ÿ’ป Developers | Build sentiment dashboards | ### ๐Ÿ“‹ What the Stocktwits Trending Symbols Scraper does - Calls `https://api.stocktwits.com/api/2/streams/trending.json`. - Aggregates messages per symbol with bullish/bearish counts. - Computes a net sentiment label. - Optionally filters to a list of tickers. - Exports as CSV, Excel, JSON, JSONL, XML, RSS, or HTML. > ๐Ÿ’ก **Why it matters:** Stocktwits is the largest dedicated retail trading community. Sentiment skew on trending tickers is a leading indicator for short-term momentum. ### ๐ŸŽฌ Full Demo _๐Ÿšง Coming soon._ ### โš™๏ธ Input
FieldTypeRequiredDescription
maxItemsintegerNoFree 10, paid up to 1M.
symbolFilterstringNoComma-separated tickers.
**Example 1:** ```json { "maxItems": 25 } ```` **Example 2:** ```json { "symbolFilter": "AAPL,TSLA,NVDA" } ``` > โš ๏ธ **Good to Know:** The trending endpoint is rate-limited. Each call returns up to ~30 most recent trending messages. ### ๐Ÿ“Š Output | Field | Type | Description | |---|---|---| | ๐Ÿ“ˆ `symbol` | string | Ticker. | | ๐Ÿ“› `title` | string | Company name. | | ๐Ÿ”— `url` | string | Stocktwits symbol page. | | ๐Ÿ‘€ `watchlist_count` | number | Followers count. | | ๐Ÿ’ฌ `message_count` | number | Messages in current trending window. | | ๐ŸŽญ `sentiment` | string | Bullish / Bearish / Neutral skew. | | ๐Ÿ’ฒ `last_price` | number | Last sale (if present). | | ๐Ÿ“Š `change` | number | Day change. | | ๐Ÿ•’ `scrapedAt` | string | When fetched. | | โŒ `error` | string | Error if upstream failed. | **Sample record:** ```json { "symbol": "TSLA", "title": "Tesla Inc.", "url": "https://stocktwits.com/symbol/TSLA", "watchlist_count": 540123, "message_count": 12, "sentiment": "Bullish", "bullish_messages": 9, "bearish_messages": 2, "last_price": 241.5, "change": 3.21, "scrapedAt": "2026-05-29T13:00:00.000Z", "error": null } ``` ### โœจ Why choose this Actor | ๐Ÿ†“ | Public Stocktwits trending stream, no key. | | ๐ŸŽญ | Auto-aggregated bullish/bearish skew. | | ๐Ÿ”ข | Numeric casting. | | ๐Ÿ›Ÿ | Errors surfaced cleanly. | | ๐Ÿ”Œ | Symbol filter. | | ๐Ÿ’พ | CSV / Excel / JSON / XML / RSS / HTML. | ### ๐Ÿ“ˆ How it compares to alternatives | Approach | Setup | Sentiment agg? | Filter? | Errors? | |---|---|---|---|---| | Raw fetch | 20 min | manual | โŒ | โŒ | | Custom pipeline | 1 hr | partial | partial | partial | | **This Actor** | 5 sec | โœ… | โœ… | โœ… | ### ๐Ÿš€ How to use 1. Click **Try for free**. 2. Optional `symbolFilter`. 3. Click **Start**. ### ๐Ÿ’ผ Business use cases **๐Ÿ“Š Meme-stock detection.** Catch breakout names before they hit mainstream news. **๐Ÿ’ผ Quant signals.** Use sentiment skew as a backtestable feature. **๐Ÿ“ฐ Newsroom.** Spot mood swings before earnings. **๐Ÿค– ML.** Train sentiment models with crowd labels. ### ๐Ÿ”Œ Automating Stocktwits Trending Symbols Scraper - **Make / Zapier** to Airtable / Slack. - **Cron schedule** native Apify. - **Webhooks** on completion. - **Pipe to BigQuery / Snowflake / Postgres**. ### ๐ŸŒŸ Beyond business use cases **๐ŸŽ“ Education.** Teach sentiment analysis. **๐Ÿงช Personal research.** Track your watchlist. **๐Ÿค Open data.** Retail sentiment dashboards. **๐Ÿงฐ Prototyping.** Quick feed. ### ๐Ÿค– Ask an AI assistant about this scraper Drop this README into ChatGPT or Claude. ### โ“ Frequently Asked Questions **โ“ API key?** None. **โ“ Refresh?** Real-time trending stream. **โ“ Filter?** Yes by symbol. **โ“ Cast?** Yes. **โ“ Errors?** Clean `{error}` record. **โ“ Schedule?** Yes. **โ“ Scraping or API?** Public API. **โ“ Schema stable?** Yes. **โ“ Formats?** CSV, Excel, JSON, JSONL, XML, RSS, HTML. **โ“ How fresh?** Last ~30 trending messages. ### ๐Ÿ”Œ Integrate with any app Apify integrations with Make, Zapier, Slack, Discord, Google Drive, Google Sheets, Gmail, Airbyte, Keboola, Telegram, GitHub, REST/webhook. ### ๐Ÿ”— Recommended Actors | Actor | What it does | |---|---| | [ParseForge Alpha Vantage Public Scraper](https://apify.com/parseforge/alpha-vantage-public-scraper) | Stocks, FX, crypto. | | [ParseForge PredictIt Markets Scraper](https://apify.com/parseforge/predictit-markets-scraper) | Political prediction markets. | | [ParseForge Metaculus Questions Scraper](https://apify.com/parseforge/metaculus-questions-scraper) | Forecasting questions. | | [ParseForge The Odds API Sports Scraper](https://apify.com/parseforge/the-odds-api-sports-scraper) | Sports betting markets. | > ๐Ÿ’ก **Pro Tip:** browse the complete [ParseForge collection](https://apify.com/parseforge) for 900+ scrapers. *** **Disclaimer:** This actor scrapes only publicly available data. ParseForge is not affiliated with, endorsed by, or sponsored by any of the third-party services referenced. Users are responsible for complying with the target site's terms of service and applicable law. [Create a free account w/ $5 credit](https://console.apify.com/sign-up?fpr=vmoqkp). # Actor input Schema ## `maxItems` (type: `integer`): Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000 ## `symbolFilter` (type: `string`): Comma-separated ticker symbols (e.g. AAPL,TSLA). Empty = all trending. ## Actor input object example ```json { "maxItems": 10 } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("parseforge/stocktwits-trending-symbols-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "maxItems": 10 } # Run the Actor and wait for it to finish run = client.actor("parseforge/stocktwits-trending-symbols-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "maxItems": 10 }' | apify call parseforge/stocktwits-trending-symbols-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=parseforge/stocktwits-trending-symbols-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Stocktwits Trending Symbols Scraper", "description": "Pull trending tickers from the Stocktwits public feed with symbol, watchlist_count, message_count, sentiment, last_price, and change. Optionally filter by tickers like AAPL or TSLA. Useful for retail sentiment tracking, momentum screening, and meme stock research.", "version": "0.1", "x-build-id": "pCsJ7eQAmkgyHLp9O" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/parseforge~stocktwits-trending-symbols-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-parseforge-stocktwits-trending-symbols-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/parseforge~stocktwits-trending-symbols-scraper/runs": { "post": { "operationId": "runs-sync-parseforge-stocktwits-trending-symbols-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/parseforge~stocktwits-trending-symbols-scraper/run-sync": { "post": { "operationId": "run-sync-parseforge-stocktwits-trending-symbols-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "maxItems": { "title": "Max Items", "minimum": 1, "maximum": 1000000, "type": "integer", "description": "Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000" }, "symbolFilter": { "title": "Symbol filter (optional)", "type": "string", "description": "Comma-separated ticker symbols (e.g. AAPL,TSLA). Empty = all trending." } } }, "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 } } } } } } } } } } ```