# Reddit Sentiment Analyzer (`echocall/reddit-sentiment-analyzer`) Actor

Analyzes the sentiment (positive/negative/neutral) of Reddit posts for any subreddit.

- **URL**: https://apify.com/echocall/reddit-sentiment-analyzer.md
- **Developed by:** [Kristian Gasic](https://apify.com/echocall) (community)
- **Categories:** Automation, Lead generation, Other
- **Features:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.00 / 1,000 results

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/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

## Reddit Sentiment Analyzer 🚀📊

**Apify Actor** – Analyzes sentiment of Reddit posts for brand monitoring, market research, and trend analysis.

### What does this Actor do?

The **Reddit Sentiment Analyzer** scrapes posts from any subreddit and automatically performs sentiment analysis. Each post is classified as **positive**, **negative**, or **neutral**, enabling quick market sentiment checks and strategic insights.

Perfect for:

- **Investor sentiment analysis** – Track bullish/bearish sentiment in `r/stocks`, `r/wallstreetbets`, `r/cryptocurrency`
- **Brand monitoring** – See what Reddit says about your product or competitor
- **Trend detection** – Identify emerging topics and community sentiment shifts
- **Market research** – Fast-track consumer feedback at scale

### How it works

1. Fetches posts from your chosen subreddit
2. Uses **Puppeteer + Residential Proxy** to bypass Reddit's IP blocks
3. Falls back to **Reddit's JSON API** if needed (always reliable)
4. Analyzes text sentiment using industry-standard NLP
5. Outputs individual post data + summary statistics

### Input Parameters

| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| `subreddit` | string | ✅ | — | Subreddit name (e.g., `stocks`, `wallstreetbets`) |
| `query` | string | ❌ | empty | Search term to filter posts (e.g., `Tesla`). Leave empty for all posts. |
| `limit` | number | ❌ | 50 | Number of posts to fetch (1–200) |
| `sortBy` | enum | ❌ | `new` | How to sort: `hot`, `new`, or `top` |

#### Example Input

```json
{
  "subreddit": "stocks",
  "query": "Tesla",
  "limit": 50,
  "sortBy": "new"
}
```

### Output

The Actor saves two types of data to the dataset:

#### 1. Individual Post Items (one per post)

```json
{
  "id": "abc123",
  "title": "Is Tesla still a good buy?",
  "score": 120,
  "numComments": 45,
  "url": "https://reddit.com/r/stocks/comments/abc123",
  "createdUtc": "2026-06-08T12:00:00.000Z",
  "sentiment": {
    "score": -3,
    "comparative": -0.25,
    "label": "negative",
    "tokens": ["bad", "worried", "overpriced"]
  },
  "overallSentiment": "Negative sentiment (score: -3) with keywords: bad, worried, overpriced"
}
```

#### 2. Summary Item (final analysis)

```json
{
  "type": "summary",
  "subreddit": "stocks",
  "query": "Tesla",
  "sortBy": "new",
  "totalPostsAnalyzed": 50,
  "averageSentiment": 1.2,
  "positiveCount": 18,
  "negativeCount": 12,
  "neutralCount": 20,
  "topPositivePost": {"title": "...", "url": "..."},
  "topNegativePost": {"title": "...", "url": "..."}
}
```

### Important: Residential Proxy Requirement

⚠️ **This Actor uses Apify Residential Proxies** – Reddit blocks all datacenter IPs.

- Real ISP IPs guarantee access (no 403 errors)
- Essential for reliable automation
- Factor proxy costs into your usage plan
- Runs only in Apify cloud (not locally without proxy setup)

### Limits & Fair Use

- ✅ **Max 200 posts** per run
- ✅ Works with **public & restricted subreddits**
- ✅ Gracefully handles errors (404, private communities, empty subreddits)
- ✅ Sentiment analysis optimized for **English text**
- ✅ Respects Reddit's terms of service (no authentication bypass, no rate limiting)

### Local Testing

```bash
## Install dependencies
npm install

## Start a local Apify run
apify run
```

You will be prompted for a `subreddit` name (input from `INPUT_SCHEMA.json`).

### Deployment to Apify

```bash
## Push the Actor to the Apify Console
apify push
```

Then in the **Apify Console**:

1. Navigate to your Actor.
2. Click **"Publish to Store"**.
3. Choose **"Pay-per-event"** as monetization.
4. Suggested price: **$1.99 per 100 analyzed posts**.

### Tech Stack

- **[Crawlee](https://crawlee.dev/)** – `CheerioCrawler` for HTTP requests and scraping
- **[sentiment](https://www.npmjs.com/package/sentiment)** – AFINN-based sentiment analysis for Node.js
- **[Apify SDK](https://docs.apify.com/sdk/js/)** – Dataset management & Actor runtime
- Optional: **[franc](https://www.npmjs.com/package/franc)** – Language detection to filter non-English posts

### License

MIT

# Actor input Schema

## `subreddit` (type: `string`):

Name of the subreddit to analyze, e.g. 'stocks', 'wallstreetbets', 'cryptocurrency'.

## `query` (type: `string`):

Optional search term to filter posts, e.g. 'Tesla'. If empty, the newest/latest posts are fetched.

## `limit` (type: `integer`):

Maximum number of posts to analyze (default: 50, max: 200).

## `sortBy` (type: `string`):

How to sort the Reddit posts.

## Actor input object example

```json
{
  "subreddit": "stocks",
  "query": "",
  "limit": 50,
  "sortBy": "new"
}
```

# 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 = {
    "subreddit": "stocks",
    "query": ""
};

// Run the Actor and wait for it to finish
const run = await client.actor("echocall/reddit-sentiment-analyzer").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 = {
    "subreddit": "stocks",
    "query": "",
}

# Run the Actor and wait for it to finish
run = client.actor("echocall/reddit-sentiment-analyzer").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 '{
  "subreddit": "stocks",
  "query": ""
}' |
apify call echocall/reddit-sentiment-analyzer --silent --output-dataset

```

## MCP server setup

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

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/sFWSNyaxEaJ088HZ2/builds/Ls1veYcqolcrWQnNh/openapi.json