# YouTube Video Comment Sentiment Signals (`neuton/youtube-video-comment-sentiment-signals`) Actor

Get complete source-linked public comments with transparent lexical sentiment evidence for brand research teams, creator agencies, community analysts, and competitive-intelligence workflows.

- **URL**: https://apify.com/neuton/youtube-video-comment-sentiment-signals.md
- **Developed by:** [Neuton Scripts](https://apify.com/neuton) (community)
- **Categories:** Social media, Marketing, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$25.00 / 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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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 Video Comment Sentiment Signals

Get complete source-linked public comments with transparent lexical sentiment evidence for brand research teams, creator agencies, community analysts, and competitive-intelligence workflows. The Actor uses bounded public YouTube sources without login.

### Buyer question

**What transparent positive, negative, and neutral lexical signals appear in these public comments?**

### Start in 30 seconds

```json
{
  "videoUrlsOrIds": [
    "dQw4w9WgXcQ"
  ],
  "maxCommentsPerVideo": 20,
  "maxResults": 20
}
```

[Open the workflow-specific starter Task](https://apify.com/neuton/youtube-video-comment-sentiment-signals/examples/sample-yt-comment-sentiment-rick-astley?utm_source=apify_store\&utm_medium=actor_readme\&utm_campaign=youtube_comment_sentiment_activation\&utm_content=lexical_sentiment_task), run the bounded sample, inspect the Dataset and free `RUN_SUMMARY`, then replace the sample input.

### Choose this Actor when

Choose this specialist when you need complete source-linked public comments with transparent lexical sentiment evidence with explicit evidence and billing boundaries. It is intentionally narrower than a generic YouTube scraper. Start with one query, video, channel, or playlist before scheduling a larger workflow.

### First run checklist

1. Run the included bounded public example.
2. Verify source URLs, IDs, text, and evidence fields in the Dataset.
3. Compare paid rows with the free `RUN_SUMMARY`.
4. Save a Task, schedule, webhook, API, MCP, or AI-agent workflow only after the sample is useful.

### Evidence and billing

Launch PPE price: **$25.00 per 1,000 complete source-linked public comments with transparent lexical sentiment evidence**, or **$2.50 for 100**. Diagnostics, failed or incomplete fetches, duplicates, empty searches, unsupported classifications, and truncated records are never billed.

Use a disclosed deterministic lexical score over the public comment text. Label ties as neutral and never infer emotion, identity, demographics, purchase intent, or author characteristics.

### Output schema

Billable Dataset fields: `videoId`, `videoUrl`, `commentId`, `commentUrl`, `authorName`, `commentText`, `sentiment`, `sentimentScore`, `positiveTerms`, `negativeTerms`, `sentimentMethod`, `evidenceDirect`, `scrapedAt`. The separate `RUN_SUMMARY` reports requested inputs, saved rows, free failures, and source boundaries. Error-only or placeholder rows never enter the Dataset.

### Source boundaries

The Actor uses public YouTube search, comment, channel metadata, or playlist-feed surfaces as required by this exact workflow. Cloud runs use Apify's plan-included rotating datacenter proxy because YouTube can require sign-in from shared Actor IPs. It never uses a residential proxy and does not return captions, transcripts, subtitles, private videos, members-only content, logged-in data, or inferred audience demographics.

### Automation and AI agents

Use Apify Tasks, schedules, API, webhooks, ChatGPT, Claude, Neuton Actors MCP, n8n, Make, Zapier, Sheets, a warehouse, RAG pipeline, or agent workflow.

Hosted Apify MCP endpoint: `https://mcp.apify.com/?tools=neuton/youtube-video-comment-sentiment-signals`

### Explore the YouTube data family

- [YouTube Video Metadata Scraper](https://apify.com/neuton/youtube-video-metadata-scraper) for complete raw video fields
- [YouTube Description Links Intelligence](https://apify.com/neuton/youtube-description-links-intelligence) for explicit outbound links
- [Neuton Actors MCP](https://apify.com/neuton/neuton-actors-mcp-server) for AI-agent workflows

### SEO keywords

YouTube comment sentiment, creator audience signals, lexical sentiment evidence, video community analysis, creator intelligence, Apify YouTube Actor.

### Responsible use

Use public data for legitimate creator, media, marketing, research, education, moderation, and automation workflows. Do not bypass access controls, collect private content, identify anonymous people, infer sensitive traits, or make consequential decisions from lexical sentiment. Review YouTube's current terms and applicable privacy, advertising, and copyright rules before production use.

# Actor input Schema

## `videoUrlsOrIds` (type: `array`):

Public YouTube watch URLs, Shorts URLs, or 11-character video IDs. Up to 10.

## `maxResults` (type: `integer`):

Maximum complete unique paid rows saved across all inputs.

## `maxCommentsPerVideo` (type: `integer`):

Bounded maximum inspected for each supplied input.

## Actor input object example

```json
{
  "videoUrlsOrIds": [
    "dQw4w9WgXcQ"
  ],
  "maxResults": 20,
  "maxCommentsPerVideo": 20
}
```

# Actor output Schema

## `results` (type: `string`):

No description

## `summary` (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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("neuton/youtube-video-comment-sentiment-signals").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("neuton/youtube-video-comment-sentiment-signals").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call neuton/youtube-video-comment-sentiment-signals --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,neuton/youtube-video-comment-sentiment-signals"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/7zQwxfzsdiVqKKoLL/builds/IQr1PGn3avldeollS/openapi.json