Reddit User Data Scraper (Apify Actor) 🚀

Collect rich Reddit user profiles and activity data at scale. This actor fetches user submissions and interactions into clean JSON so you can analyze posting patterns, engagement, media, and communities without brittle browser automation.

Why choose this Reddit scraper

• Purpose‑built for users: Focused endpoint for user data to keep responses consistent and fast.
• Robust & scalable: Built on Apify with retry logic and key rotation to minimize failures.
• Clean output: Normalized JSON and automatic removal of any non‑data fields.
• Easy to run: Simple, documented inputs. Plug into datasets, exports, and downstream BI.

What you can do

• User research: Map posting cadence, topics, and engagement over time.
• Community analysis: See where a user is most active and what resonates.
• Content pipelines: Feed analytics dashboards, moderation tools, or research workflows.

Input parameters

Key	Type	Editor	Default	Notes
username	string	textfield	—	Target Reddit username (without u/). Required.
filter	string	select	posts	The type of content to filter: posts, comments, media, users, communities. users and communities are sitewide only.
sortType	string	select	relevance	Sorting: relevance, hot, top, new, comments.
cursor	string	textfield	—	Pagination cursor for the next page, e.g. t3_1btflsp.

Usage examples

Basic user fetch 🧑‍💻

{
  "username": "popculturechat",
  "filter": "posts",
  "sortType": "new"
}

Paginating with cursor ⏭️

Use the cursor value returned in the response to fetch the next page.

{
  "username": "popculturechat",
  "filter": "posts",
  "sortType": "relevance",
  "cursor": "t3_1btflsp"
}

Output format

• The actor pushes one or more JSON records to the default Apify dataset.

Example (truncated):

{
  "username": "popculturechat",
  "filter": "posts",
  "sortType": "new",
  "cursor_used": null,
  "fetched_at": "2025-01-01T10:00:00.000Z",
  "payload": {
    "user": { "name": "popculturechat", "karma": 12345 },
    "items": [ /* posts/comments/media ... */ ],
    "nextCursor": "t3_1btflsp"
  }
}

Best practices ✅

• Be respectful of platform rules: Use for compliant, public‑data use cases.
• Use cursors for large users: Always re‑use nextCursor to paginate.
• Monitor nulls: Schemas are not guaranteed; handle missing fields.
• Automate: Schedule runs and export to your data stack.

FAQ ❓

• Does it support pagination? Yes. Use the cursor parameter with the nextCursor value from the previous run.
• What content types are supported? posts, comments, media, users, communities.
• Which sort types are supported? relevance, hot, top, new, comments.
• Can I use this in Python? Yes. Export the dataset in JSON/CSV and load with your preferred tools.
• Is private data included? No. Only public data is returned.

Keywords

#RedditScraper #RedditUserData #RedditAnalytics #RedditAPIAlternative #RedditDataPipeline #RedditPosts #RedditComments #RedditCommunities #RedditMedia #ApifyActor #WebScraping #DataEngineering #OpenData