# Stock Sentiment Score API: Reddit, X, News & YouTube (`sentisense/stock-sentiment-score`) Actor

Daily social sentiment Score per US stock from Reddit, X, YouTube, Hacker News and Substack, blended with news, plus 30-day trend, mention momentum and story drivers.

- **URL**: https://apify.com/sentisense/stock-sentiment-score.md
- **Developed by:** [SentiSense](https://apify.com/sentisense) (community)
- **Categories:** AI, Agents
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$50.00 / 1,000 tickers

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?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Stock Sentiment Score API: Reddit, X, News & YouTube

One sentiment number per US stock that blends social sentiment from Reddit, X, YouTube, Hacker News
and Substack with the news flow, plus the 30-day baseline that tells you whether today's reading is
unusual. Give it tickers, get one row each.

**Who it is for**

- Traders who want a market-mood read on a watchlist before the open, without scraping six sites.
- Analysts and quant researchers who need a consistent daily sentiment series to join to prices.
- AI agents that need sentiment as one structured row instead of a thousand posts to summarize.
- Developers who wanted Stocktwits API access and cannot get it. This actor carries no Stocktwits
  data, but it answers the same question, what the crowd is saying about a ticker and which way it
  leans, from Reddit, X, YouTube, Hacker News, Substack and news, as one composite Score.

**What you get per ticker**

- **SentiSense Score**: a 0-centered composite of tone and mention volume. Positive means the
  conversation leans bullish and is loud enough to matter. Today's reading, the 30-day average, the
  30-day change, and a seven-band label from Strong Bearish to Strong Bullish.
- **Direction and trend**: Bullish, Neutral or Bearish, plus UP, DOWN or FLAT.
- **Mention momentum**: today's mention count against the 30-day daily average, and share of voice.
- **Per-source tone**: how News, Reddit, X, YouTube, Hacker News and Substack each lean, loudest
  source first, with each source's share of the mentions.
- **Story drivers** with their own tone, and a **narrative** explaining why the Score sits where it does.

Built by SentiSense, which ingests news, social media and market data all day and distills it with AI.

Data by [SentiSense](https://sentisense.ai). API docs: [sentisense.ai/docs/api](https://sentisense.ai/docs/api/).

### Input

| Field | Type | Default | Notes |
|---|---|---|---|
| `tickers` | string\[] | required | US stock or ETF symbols, e.g. `["NVDA", "TSLA"]`. Up to 25 per run, case-insensitive, duplicates removed. |
| `includeDrivers` | boolean | `true` | Include the top stories driving each ticker, each with a tone reading. |

### Output

One dataset row per ticker. Illustrative row, every value invented, `bySource` shortened:

```json
{
  "ticker": "NVDA", "companyName": "NVIDIA Corporation", "asOf": "2025-11-03",
  "sentisenseScore": 18.7, "sentisenseScoreAvg30d": 24.1, "sentisenseScoreDelta30d": -3.6,
  "scoreLabel": "Bullish", "direction": "Bullish", "latestDirection": "Slightly Bullish", "trend": "DOWN",
  "mentions": 1420, "mentionsAvg30d": 1185.0, "socialDominance": 0.031,
  "bySource": [
    {"source": "News", "direction": "Bullish", "mentionShare": 58, "value": 0.22},
    {"source": "Reddit", "direction": "Neutral", "mentionShare": 27, "value": 0.03},
    {"source": "Hacker News", "direction": "Neutral", "mentionShare": 4, "value": 0.05}
  ],
  "drivers": [{"title": "Example headline about a product launch", "tone": 0.41}],
  "narrative": "Example narrative explaining the reading."
}
```

Reading the fields:

- `sentisenseScore` and `latestDirection` are **today's** reading; `sentisenseScoreAvg30d`, `scoreLabel`
  and `direction` describe the **30-day regime**. Before today's reading lands, the two today fields are
  `null` and the regime fields still answer.
- `scoreLabel` bands: Strong Bearish, Bearish, Slightly Bearish, Neutral, Slightly Bullish, Bullish,
  Strong Bullish. `direction` collapses them to three.
- `bySource[].value` is tone on -1 to +1; `mentionShare` is a whole-number percent summing to 100.
  `socialDominance` is a fraction of all tracked conversation (`0.031` = 3.1%), `null` when no signal.
- Uncovered tickers return `{"ticker": "XYZ", "error": "no_coverage"}`; failed requests return
  `"error": "request_failed"` or `"http_<status>"`. Neither is charged.

### Pricing

$0.05 per ticker analyzed, charged only when a ticker returns a sentiment row. No coverage or a failed
request costs nothing. A 25-ticker run with 23 covered names costs $1.15.

### FAQ

**How fresh is the data?** The Score is a daily reading, not a live feed: it is recomputed once a day
and today's reading lands late morning US Eastern time (later on weekends). Before that,
`sentisenseScore` and `latestDirection` are `null` while the 30-day fields are complete, so a
pre-market run still gives a usable regime read.

**Which tickers are covered?** US-listed stocks and ETFs tracked by the data source. The cheapest check
is to run the symbol: an uncovered one comes back as a free `no_coverage` row.

**Does it work for ETFs?** Yes. A tracked ETF such as SPY returns the same sentiment row as a stock
and is charged like any other analyzed ticker.

**Does it include Stocktwits?** No. There is no Stocktwits data in this actor: no posts, no message
stream, no bullish or bearish tags from that service, and no affiliation with it. The social side of
the Score comes from Reddit, X, YouTube, Hacker News and Substack, with news alongside. If you cannot
get Stocktwits API access and the question you need answered is which way the crowd leans on a
ticker, this is one way to get that read as a daily number.

**How much of the Score is social?** It varies by ticker, and `bySource[].mentionShare` tells you for
each one. On most large caps News carries the largest share, often two thirds to three quarters, with
Reddit and X next. On retail favorites Reddit can carry most of the conversation. A small source can show a share
of 0 or 1 percent on a quiet day.

**What does `no_coverage` mean?** The symbol is not tracked. It is not an outage. Check the spelling and
that it is a US listing. That row is not charged.

**How often should I run it?** Once a day after late morning US Eastern for a fresh Score; hourly runs
buy the same Score again. Mention counts and drivers can move intraday if you want those.

**Is the Score the same as sentiment?** No. Per-source tone is a -1 to +1 polarity. The Score is
volume-aware and unbounded, so a mildly positive name with a mention surge can outscore a quietly adored
one. Compare Scores to Scores and tone to tone.

Educational and informational use only. Not investment advice.

# Actor input Schema

## `tickers` (type: `array`):

US stock or ETF tickers to analyze, e.g. NVDA, TSLA, SPY. Up to 25 per run, case-insensitive, duplicates removed.

## `includeDrivers` (type: `boolean`):

Include the top news stories driving each ticker's sentiment, each with its own tone reading.

## Actor input object example

```json
{
  "tickers": [
    "NVDA",
    "TSLA"
  ],
  "includeDrivers": true
}
```

# Actor output Schema

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

One row per requested ticker, in the default dataset.

# 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 = {
    "tickers": [
        "NVDA",
        "TSLA"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("sentisense/stock-sentiment-score").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 = { "tickers": [
        "NVDA",
        "TSLA",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("sentisense/stock-sentiment-score").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 '{
  "tickers": [
    "NVDA",
    "TSLA"
  ]
}' |
apify call sentisense/stock-sentiment-score --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,sentisense/stock-sentiment-score"
        }
    }
}
```

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/0XURvpZhkys40ig8Q/builds/GwuTdcTfkBOCP2Tb5/openapi.json