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.

Run a verified example

Find rising AI posts in technology opens a ready-to-run public task with bounded costs and ranked output.

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.

{
  "queries": [
    "ai"
  ],
  "subreddits": [
    "technology"
  ],
  "lookbackHours": 720,
  "maxPosts": 5,
  "maxItems": 5
}

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.

Use it as an MCP tool

Connect this Actor to ChatGPT, Codex, Claude, Cursor, or another MCP client through Apify’s hosted MCP server:

"mcpServers": {
    "signal-lab-reddit-trends": {
      "url": "https://mcp.apify.com?tools=signal_lab/reddit-trend-finder"
    }
  }
}\n```

Apify opens its OAuth flow on first connection, so no API token needs to be pasted into the configuration. Ask the client for a bounded result, for example: “Find the 20 fastest-rising AI posts from r/technology in the last 72 hours and return source URLs.”

## 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.