# last30Days Trend Intel — Multi-Platform Research Reports (`openclawai/30days-trend-intel`) Actor Research any topic across Reddit, TikTok, Instagram, YouTube, HN, Polymarket, GitHub, and more. Get AI-synthesized trend briefs with engagement scores, sentiment analysis, and source citations. - **URL**: https://apify.com/openclawai/30days-trend-intel.md - **Developed by:** [Pika Choo](https://apify.com/openclawai) (community) - **Categories:** AI, Lead generation, Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $0.35 / standard report This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## 30Days Trend Intel — Multi-Platform Research Reports Research any topic across **13+ platforms** in one run. Get scored, clustered results with optional AI synthesis. ### Who needs this? - **Marketers** — track brand mentions, competitor moves, trending topics - **Researchers** — cross-platform analysis with engagement scores and citations - **Sales teams** — know what prospects are talking about before the call - **Content creators** — find viral topics and best takes across platforms - **Investors** — sentiment analysis + Polymarket prediction odds - **Product managers** — understand user feedback across communities ### Platforms searched | Platform | What you get | |----------|-------------| | **Reddit** | Top posts, comments, upvote counts, subreddit breakdown | | **TikTok** | Viral videos, view counts, transcripts, creator profiles | | **Instagram** | Reels, engagement metrics, spoken-word transcripts | | **YouTube** | Top videos, transcripts, view counts, channel analysis | | **Hacker News** | Technical discussions, points, comment threads | | **Polymarket** | Prediction market odds backed by real money | | **GitHub** | Repos, PRs, stars, release notes, contributor activity | | **Threads** | Post-Twitter conversations from creators and brands | | **Pinterest** | Visual discovery, pins, saves, product trends | | **Bluesky** | Decentralized social posts from the AT Protocol | ### Features - **Multi-source scoring** — results ranked by real engagement (upvotes, views, likes), not SEO - **Cross-source clustering** — same story on Reddit + YouTube + X gets merged into one insight - **AI synthesis** — executive summary, key findings, sentiment, best viral quotes - **4 depth tiers** — from quick scan ($0.15) to full deep research ($1.50) - **Flexible timeframes** — last 7, 14, 30, or 90 days - **JSON + Markdown output** — structured data for pipelines or readable reports ### Pricing | Tier | Price | What's included | |------|-------|----------------| | Quick Scan | $0.15 | Reddit, HN, Polymarket, GitHub | | Standard | $0.35 | + TikTok, Instagram, YouTube | | Deep Intel | $0.75 | More results per source + comments + transcripts | | Full Brief | $1.50 | Everything + AI web grounding via Perplexity | ### Input example ```json { "topic": "OpenAI vs Anthropic", "depth": "standard", "timeframe": "30d", "aiSynthesis": true, "outputFormat": "json" } ```` ### Output example ```json { "topic": "OpenAI vs Anthropic", "total_results": 47, "source_counts": { "reddit": 15, "tiktok": 8, "youtube": 6, "hackernews": 10, "polymarket": 3, "github": 5 }, "ai_synthesis": { "executive_summary": "The AI race intensified this month with Anthropic's Claude 4.6 launch...", "key_findings": [ {"finding": "Claude 4.6 outperforms GPT-5 on coding benchmarks", "source": "reddit", "engagement": "2.1K upvotes"} ], "sentiment": "mixed", "momentum": "accelerating" }, "clusters": [...], "ranked_candidates": [...] } ``` ### FAQ **How fresh is the data?** Real-time. Every run fetches live data from all platforms. **Do I need API keys?** No. Everything is included in the per-run price. **What's the difference between tiers?** Quick uses free sources only. Standard adds social video platforms. Deep gets more results + comments. Full adds AI-powered web grounding. **Can I filter by platform?** Yes — use the Sources field to select specific platforms. **What if AI synthesis fails?** You still get the full raw data with scores and clusters. AI synthesis is a bonus layer. # Actor input Schema ## `topic` (type: `string`): Any topic, person, company, product, event, or trend. Examples: 'OpenAI vs Anthropic', 'Taylor Swift Eras Tour', 'best CRM tools 2026', 'Peter Steinberger' ## `depth` (type: `string`): Quick ($0.15) = Reddit + HN + Polymarket. Standard ($0.35) = + TikTok, Instagram, YouTube. Deep ($0.75) = more results per source. Full ($1.50) = everything + Perplexity web grounding. ## `timeframe` (type: `string`): How far back to search ## `sources` (type: `array`): Select specific platforms to search, or leave empty for all available ## `aiSynthesis` (type: `boolean`): Generate an AI-powered executive summary with key findings, sentiment, and best takes ## `outputFormat` (type: `string`): JSON for programmatic use, Markdown for readable reports ## `proxyConfiguration` (type: `object`): Residential proxies prevent Reddit/platform 403 blocks. 📌 Default: Apify Residential Proxy ($8/GB) 💡 Alternative: BUYPROXIES94952 (free datacenter, less reliable) ## Actor input object example ```json { "topic": "Apify web scraping", "depth": "standard", "timeframe": "30d", "aiSynthesis": true, "outputFormat": "json", "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "topic": "Apify web scraping", "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("openclawai/30days-trend-intel").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "topic": "Apify web scraping", "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("openclawai/30days-trend-intel").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 '{ "topic": "Apify web scraping", "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call openclawai/30days-trend-intel --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=openclawai/30days-trend-intel", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "last30Days Trend Intel — Multi-Platform Research Reports", "description": "Research any topic across Reddit, TikTok, Instagram, YouTube, HN, Polymarket, GitHub, and more. Get AI-synthesized trend briefs with engagement scores, sentiment analysis, and source citations.", "version": "1.0", "x-build-id": "q2wpRGCsu9b8ghfZi" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/openclawai~30days-trend-intel/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-openclawai-30days-trend-intel", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/openclawai~30days-trend-intel/runs": { "post": { "operationId": "runs-sync-openclawai-30days-trend-intel", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/openclawai~30days-trend-intel/run-sync": { "post": { "operationId": "run-sync-openclawai-30days-trend-intel", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "topic" ], "properties": { "topic": { "title": "🔍 Research Topic", "type": "string", "description": "Any topic, person, company, product, event, or trend. Examples: 'OpenAI vs Anthropic', 'Taylor Swift Eras Tour', 'best CRM tools 2026', 'Peter Steinberger'" }, "depth": { "title": "📈 Report Depth", "enum": [ "quick", "standard", "deep", "full" ], "type": "string", "description": "Quick ($0.15) = Reddit + HN + Polymarket. Standard ($0.35) = + TikTok, Instagram, YouTube. Deep ($0.75) = more results per source. Full ($1.50) = everything + Perplexity web grounding.", "default": "standard" }, "timeframe": { "title": "📅 Timeframe", "enum": [ "7d", "14d", "30d", "90d" ], "type": "string", "description": "How far back to search", "default": "30d" }, "sources": { "title": "🌐 Sources (optional — leave empty for all)", "type": "array", "description": "Select specific platforms to search, or leave empty for all available", "items": { "type": "string", "enum": [ "reddit", "tiktok", "instagram", "youtube", "hackernews", "polymarket", "github", "threads", "pinterest", "bluesky" ], "enumTitles": [ "Reddit", "TikTok", "Instagram", "YouTube", "Hacker News", "Polymarket", "GitHub", "Threads", "Pinterest", "Bluesky" ] } }, "aiSynthesis": { "title": "🤖 AI Synthesis", "type": "boolean", "description": "Generate an AI-powered executive summary with key findings, sentiment, and best takes", "default": true }, "outputFormat": { "title": "📄 Output Format", "enum": [ "json", "markdown" ], "type": "string", "description": "JSON for programmatic use, Markdown for readable reports", "default": "json" }, "proxyConfiguration": { "title": "🌐 Proxy Configuration", "type": "object", "description": "Residential proxies prevent Reddit/platform 403 blocks.\n\n📌 Default: Apify Residential Proxy ($8/GB)\n💡 Alternative: BUYPROXIES94952 (free datacenter, less reliable)", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } } }, "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 } } } } } } } } } } ```