# Reddit Trend Finder – Rising Posts (`signal_lab/reddit-trend-finder`) Actor

Find rising Reddit posts by keyword and subreddit with engagement velocity, age-adjusted trend scores, and source links. No API key or login.

- **URL**: https://apify.com/signal\_lab/reddit-trend-finder.md
- **Developed by:** [Signal Lab](https://apify.com/signal_lab) (community)
- **Categories:** Social media
- **Stats:** 2 total users, 1 monthly users, 50.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.00 / 1,000 reddit trend 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/platform/actors/running/actors-in-store#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

## Reddit Trend Finder – Rising Posts

Find rising Reddit posts before a simple top-score sort would surface them. This Actor queries public Reddit data first, falls back to a public archive when needed, calculates engagement velocity and an age-adjusted trend score, and returns a ranked dataset—without a Reddit API key or login.

### What you can do

- Discover fast-growing discussions for content and newsletter research.
- Monitor topics inside selected subreddits.
- Rank posts by momentum instead of lifetime score.
- Export clean JSON, CSV, or Excel rows; schedule runs and connect webhooks.

### Start quickly

Start with 10–20 posts and a 72–168 hour window. Add subreddit names without `r/`; leave `subreddits` empty to search across available sources.

```json
{
  "queries": [
    "artificial intelligence"
  ],
  "subreddits": [
    "technology"
  ],
  "lookbackHours": 168,
  "maxPosts": 10,
  "maxItems": 10
}
```

1. Enter one or more phrases in `queries`.
2. Optionally narrow the search with `subreddits`.
3. Set `lookbackHours` and the hard caps `maxPosts` / `maxItems`.
4. Run the Actor, then export or schedule the dataset.

### How ranking works

The Actor sorts posts by `trendScore = (score + commentsCount × 2) / (ageHours + 2)^0.8`. Comments receive extra weight and age normalization prevents older posts from dominating. `velocityPerHour` shows raw score-plus-comment momentum per hour; `trendRank` is the final position.

### Output

Every paid result is one unique post with `trendRank`, `trendScore`, `velocityPerHour`, title, subreddit, score, comment count, age, source URL, creation time, and scrape time. The run summary records partial source failures instead of silently hiding them.

### Troubleshooting

- **No results:** broaden `lookbackHours`, remove a narrow subreddit filter, or try a shorter keyword.
- **Very recent post missing:** source indexing can lag; rerun later or use a longer window.
- **Need comments, not trend ranking:** use [Reddit Search & Comments](https://apify.com/signal_lab/reddit-search-comments).
- **Need search-demand ideas:** use [Google Autocomplete Keywords](https://apify.com/signal_lab/google-autocomplete-keywords).

### Free product guide

See the [Reddit Trend Finder workflow, use cases, and expected output](https://signal-lab-tools.vitaxastar.chatgpt.site/tools/reddit-trend-finder), or browse [all Signal Lab data tools](https://signal-lab-tools.vitaxastar.chatgpt.site).

### Pricing and responsible use

Launch pricing is **$1.00 per 1,000 successful trend results** plus the small start event shown in the Pricing tab. You pay for dataset results actually produced. Use public data responsibly and follow Reddit’s terms, privacy rules, and applicable law.

# Actor input Schema

## `queries` (type: `array`):

Search phrases to monitor.

## `subreddits` (type: `array`):

Optional subreddit names without r/.

## `lookbackHours` (type: `integer`):

How far back to search.

## `maxPosts` (type: `integer`):

Hard cap for unique posts.

## `maxItems` (type: `integer`):

Hard cap for emitted dataset rows and pay-per-event charges.

## Actor input object example

```json
{
  "queries": [
    "artificial intelligence"
  ],
  "subreddits": [
    "technology"
  ],
  "lookbackHours": 168,
  "maxPosts": 10,
  "maxItems": 10
}
```

# 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 = {
    "queries": [
        "artificial intelligence"
    ],
    "subreddits": [
        "technology"
    ],
    "lookbackHours": 168,
    "maxPosts": 10,
    "maxItems": 10
};

// Run the Actor and wait for it to finish
const run = await client.actor("signal_lab/reddit-trend-finder").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 = {
    "queries": ["artificial intelligence"],
    "subreddits": ["technology"],
    "lookbackHours": 168,
    "maxPosts": 10,
    "maxItems": 10,
}

# Run the Actor and wait for it to finish
run = client.actor("signal_lab/reddit-trend-finder").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 '{
  "queries": [
    "artificial intelligence"
  ],
  "subreddits": [
    "technology"
  ],
  "lookbackHours": 168,
  "maxPosts": 10,
  "maxItems": 10
}' |
apify call signal_lab/reddit-trend-finder --silent --output-dataset

```

## MCP server setup

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

```

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/Ql2iB4mEvuLPImSCp/builds/b7xVlzFbWG9wIS9zm/openapi.json