# Youtube Comment Scraper - Export to CSV/JSON (`epicscrapers/youtube-comments-scraper`) Actor \[$0.5/1000] ✨YouTube comments scraper to scrape, extract, export YouTube comments to CSV/JSON. YouTube comment extractor, downloader, API alternative for scraping video comments, replies, likes, author data. Bulk YouTube comments download, dataset generator. Best YouTube comment scraper without API. - **URL**: https://apify.com/epicscrapers/youtube-comments-scraper.md - **Developed by:** [Epic Scrapers](https://apify.com/epicscrapers) (community) - **Categories:** Social media, Videos, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $0.40 / 1,000 comments 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 ## YouTube Comments Scraper – Extract Comments from Any YouTube Video Extract every comment, reply, like count, and author profile from any YouTube video—at scale. Whether you need to analyze audience sentiment, moderate user discussions, collect testimonials, or build a dataset for machine learning, this actor pulls structured comment data from one video or hundreds. ### Why scrape YouTube comments? YouTube comments are a goldmine of real-world data. Marketers mine them for product feedback and trend signals. Creators analyze sentiment to understand their audience. Researchers study conversation dynamics across millions of videos. Recruiters spot emerging talent in comment sections. And brands track how their campaigns are being talked about. Manually copying comments is not viable beyond a handful of videos. This actor automates the entire process, delivering clean, structured data you can import into any tool. ### Example output ```json { "id": "UgzNF6YV0mlS2GWceOZ4AaABAg", "parent": "root", "text": "I didn't get rickrolled today, I just really enjoy this song", "like_count": 363000, "author_id": "UCA1oEnRYKBmFDAcoKso2pAA", "author": "@CinematicCaptures", "author_thumbnail": "https://yt3.ggpht.com/ytc/AIdro_m2p2NbssAK79AX2uQzEvNPnnEIAIlB-PdN9Q4GSiqP7k8=s88-c-k-c0x00ffffff-no-rj", "author_is_uploader": false, "author_is_verified": true, "author_url": "https://www.youtube.com/@CinematicCaptures", "is_favorited": false, "_time_text": "5 years ago", "timestamp": 1620950400, "video_id": "dQw4w9WgXcQ", "video_url": "https://www.youtube.com/watch?v=dQw4w9WgXcQ", "video_title": "Rick Astley - Never Gonna Give You Up (Official Video) (4K Remaster)" } ```` ### Example input ```json { "maxCommentsPerUrl": 100, "sortCommentsBy": "top", "startUrls": [ "https://www.youtube.com/watch?v=dQw4w9WgXcQ" ] } ``` ### What data does it collect? For each comment, the actor returns: - **Comment text** – the full message, including emojis - **Author name** – the display name of the channel - **Author profile URL** – direct link to the commenter's channel - **Author ID** – unique YouTube channel identifier - **Author thumbnail** – profile picture URL - **Verified status** – whether the author's channel is verified - **Uploader badge** – whether the author is the video uploader - **Like count** – how many likes the comment received - **Timestamp** – when the comment was posted (Unix + human-readable) - **Comment ID** – unique identifier, useful for threading replies - **Parent ID** – links replies to their parent comment - **Favorited status** – whether the comment was marked as a favorite - **Video ID & URL** – which video the comment belongs to - **Video title** – the title of the video ### Who is this for? - **Content creators and YouTube agencies** – understand what your audience is saying across your entire channel - **Social media marketers** – track campaign mentions, brand sentiment, and competitor discussions - **Data analysts and researchers** – build large-scale comment datasets for NLP, sentiment analysis, or academic research - **Community managers** – identify trending discussions, top-liked feedback, and potential issues - **Product teams** – extract feature requests and bug reports from relevant video discussions ### What makes it different? - **Set it and forget it** – provide the video URLs, choose your settings, and let the actor run - **Sort by top or newest** – decide whether you want the most engaged comments or the most recent discussion - **Control comments per video** – set a maximum number of comments per URL, or scrape everything - **Residential proxy support** – avoids rate limits and blocks during large extractions - **Structured output** – clean JSON ready for spreadsheets, databases, or analysis pipelines - **Multiple videos at once** – pass as many video URLs as you need in a single run ### Popular use cases - **Sentiment analysis** – classify comments as positive, negative, or neutral to gauge audience reaction - **Competitor research** – analyze what people are saying about competing channels and products - **Content ideation** – spot recurring questions and topics your audience wants you to cover - **Influencer vetting** – review engagement quality in an influencer's comment section - **Giveaway moderation** – collect and verify entries from comment-based giveaways - **Brand monitoring** – track mentions of your brand across YouTube discussions ### Getting started 1. Open the actor on Apify Console 2. Paste one or more YouTube video URLs 3. Choose your sorting order (Top or Newest) 4. Set the maximum comments to collect per video (or 0 for unlimited) 5. Run the actor 6. Export your data as JSON, CSV, Excel, or connect it to any of the 200+ integrations Your data is delivered as a clean dataset you can download, stream via API, or push directly to cloud storage, databases, and analytics tools. # Actor input Schema ## `startUrls` (type: `array`): Enter the video urls ## `sortCommentsBy` (type: `string`): Order to sort by ## `maxCommentsPerUrl` (type: `integer`): Max comments to be scraped from each URL. Enter 0 to scrape all comments. ## Actor input object example ```json { "startUrls": [ "https://www.youtube.com/watch?v=dQw4w9WgXcQ" ], "maxCommentsPerUrl": 100 } ``` # 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 = { "startUrls": [ "https://www.youtube.com/watch?v=dQw4w9WgXcQ" ], "maxCommentsPerUrl": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("epicscrapers/youtube-comments-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 = { "startUrls": ["https://www.youtube.com/watch?v=dQw4w9WgXcQ"], "maxCommentsPerUrl": 100, } # Run the Actor and wait for it to finish run = client.actor("epicscrapers/youtube-comments-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 '{ "startUrls": [ "https://www.youtube.com/watch?v=dQw4w9WgXcQ" ], "maxCommentsPerUrl": 100 }' | apify call epicscrapers/youtube-comments-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=epicscrapers/youtube-comments-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Youtube Comment Scraper - Export to CSV/JSON", "description": "[$0.5/1000] ✨YouTube comments scraper to scrape, extract, export YouTube comments to CSV/JSON. YouTube comment extractor, downloader, API alternative for scraping video comments, replies, likes, author data. Bulk YouTube comments download, dataset generator. Best YouTube comment scraper without API.", "version": "0.0", "x-build-id": "U5arrbKcNuPSXsNql" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/epicscrapers~youtube-comments-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-epicscrapers-youtube-comments-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/epicscrapers~youtube-comments-scraper/runs": { "post": { "operationId": "runs-sync-epicscrapers-youtube-comments-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/epicscrapers~youtube-comments-scraper/run-sync": { "post": { "operationId": "run-sync-epicscrapers-youtube-comments-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", "required": [ "startUrls" ], "properties": { "startUrls": { "title": "Start URLs", "minItems": 1, "uniqueItems": true, "type": "array", "description": "Enter the video urls", "default": [ "https://www.youtube.com/watch?v=dQw4w9WgXcQ" ], "items": { "type": "string" } }, "sortCommentsBy": { "title": "Sorting Order", "enum": [ "top", "new" ], "type": "string", "description": "Order to sort by" }, "maxCommentsPerUrl": { "title": "Max Comments", "type": "integer", "description": "Max comments to be scraped from each URL. Enter 0 to scrape all comments.", "default": 100 } } }, "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 } } } } } } } } } } ```