Reddit Keyword Search Scraper – Find Posts Across Reddit

Search all of Reddit by keyword and export every matching post — no login, no Reddit API key.

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Simple Input-Output Example

Input (only search is required):

{
  "search": "electric vehicles"
}

Output (one dataset row per matching post):

{
  "id": "1c8x2fq",
  "title": "Why did EV prices drop so much this year?",
  "text": "Been watching the used market since January and the swings are wild...",
  "author": "range_anxiety_99",
  "subreddit": "electricvehicles",
  "score": 1842,
  "num_comments": 431,
  "created_utc": 1745012933,
  "url": "https://www.reddit.com/r/electricvehicles/comments/1c8x2fq/why_did_ev_prices_drop_so_much_this_year/",
  "permalink": "https://reddit.com/r/electricvehicles/comments/1c8x2fq/why_did_ev_prices_drop_so_much_this_year/",
  "_query": "{\"search\":\"electric vehicles\",\"filter\":\"posts\",\"timeFilter\":\"year\",\"sortType\":\"relevance\"}"
}

Important Notes:

• You get results instantly — one search request per run, no crawling, no browser
• Pay per result — $0.0058 per post returned, and nothing for empty or failed runs
• Searches posts only (titles and self-text) — not comments, users or subreddit listings
• Optionally restrict the search to one subreddit, or leave it empty to search all of Reddit
• All data comes from public sources only — no login, no Reddit account, no official API key
• Zero matches returns an error row, not an empty dataset (see Output Examples)
• Contact: contact@endspec.net

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Full Actor Documentation

Reddit Keyword Search Scraper

Find every Reddit post that mentions your keyword. Search across all of Reddit — or inside a single subreddit — and export title, body text, author, subreddit, score, comment count, timestamp, permalink and URL.

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Overview

The Reddit Keyword Search Scraper is an Apify Actor that runs a full-text keyword search over public posts on Reddit and returns the matching posts as structured data. Whether you are monitoring brand mentions, researching a market, mining product feedback, or building a dataset for analysis, this Actor turns a keyword into a clean, exportable list of Reddit posts in seconds.

You give it a search query. It returns the posts that match, filtered by time window and ordered by the sort you choose. No Reddit account, no OAuth, no rate-limit juggling.

What You Can Do

• Search all of Reddit by keyword: Full-text search across public Reddit posts — titles and self-text
• Restrict to a single subreddit: Narrow the same keyword search to one community (e.g. only wallstreetbets)
• Filter by time window: Last hour, day, week, month, year, or all time
• Choose the sort order: Relevance, hot, new, top, or comments
• Get full post context: Title, body text, author, subreddit, score, comment count, creation timestamp, permalink and URL
• Cap your spend per run: Set the maximum number of posts to return (1–100)
• Export anywhere: Download as JSON, CSV, Excel, HTML or XML, or pull the dataset via the Apify API

What This Actor Does Not Do

Stated plainly so you can pick the right tool:

• It does not search comments. Results are posts only. A keyword that appears only in a comment thread will not match.
• It does not paginate. One run issues one search request and returns up to your limit from that single result set. It is not a bulk historical archive crawler.
• It does not browse a subreddit's feed. If you want "the newest 100 posts in r/technology" with no keyword at all, use the Reddit Subreddit Scraper instead — see Related Actors.
• It does not access private, quarantined or deleted content. Public posts only.

Data Availability

All data returned by this Actor is publicly available information. It returns only posts that their authors published publicly on Reddit and that are visible to any logged-out visitor. The Actor makes that public information easier to collect and analyze programmatically. It does not access private subreddits, direct messages, deleted posts, or any content behind a login.

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Actor Input Parameters

The Actor accepts the following input parameters:

search • Type: string • Required: Yes • Description: The keywords to search Reddit posts for. Free-text query. e.g., "electric vehicles", "noise cancelling headphones", "my saas launch"

subreddit • Type: string • Required: Optional • Default: "" (empty — searches all of Reddit) • Description: Limit the search to a single subreddit. Use the plain name without the r/ prefix. e.g., "electricvehicles", "technology"

timeFilter • Type: string (select) • Required: Optional • Default: "year" • Allowed values: hour, day, week, month, year, all • Description: Only return posts created within this time window.

sortType • Type: string (select) • Required: Optional • Default: "relevance" • Allowed values: relevance, hot, new, top, comments • Description: The order search results are returned in.

limit • Type: integer • Required: Optional • Default: 25 • Minimum: 1 • Maximum: 100 • Description: Maximum number of posts to return. Fewer may be returned if the query matches less.

Important Notes:

• search is the only required field — everything else has a working default. {"search": "your keyword"} is a complete, valid input.
• Do not include the r/ prefix in subreddit. Use "technology", not "r/technology". The prefix is passed through verbatim and will simply match nothing.
• Leave subreddit empty to search all of Reddit. An empty string is treated as "no restriction", not as a subreddit named "".
• limit is a cap, not a quota. It is the maximum returned, not a guarantee. A narrow query, a short timeFilter, or a small subreddit will return fewer — and you are only charged for what you actually receive.
• Results are posts, always. The post/comment distinction is fixed by the Actor; there is no input that switches it to comments.
• A tighter timeFilter is a different search, not a filter applied afterwards. hour on a low-volume keyword frequently matches nothing at all. If you get no results, widen it before assuming the query is wrong.

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Input Examples

Example 1: Simple Keyword Search Across All of Reddit

{
  "search": "electric vehicles"
}

When to use: The everyday case. Searches all of Reddit, last year, by relevance, returns up to 25 posts. Best starting point for any new query.

Example 2: Brand Monitoring — Recent Mentions Only

{
  "search": "acme analytics",
  "timeFilter": "week",
  "sortType": "new",
  "limit": 100
}

When to use: Scheduled monitoring. sortType: "new" plus a short timeFilter surfaces fresh mentions in posting order, which is what you want when you run this daily or weekly and deduplicate on id.

Example 3: Keyword Search Inside a Single Subreddit

{
  "search": "index funds",
  "subreddit": "personalfinance",
  "timeFilter": "all",
  "sortType": "top",
  "limit": 50
}

When to use: Research inside one community. timeFilter: "all" with sortType: "top" returns that subreddit's highest-scoring discussions of the topic across its whole history — a good way to find canonical threads.

Example 4: A Common Mistake — the r/ Prefix

{
  "search": "index funds",
  "subreddit": "r/personalfinance"
}

Result: No results. The r/ prefix is not stripped for you — the search is restricted to a community literally named r/personalfinance, which does not exist. The run emits the "no results" error row shown in Output Example 4, and you are not charged. Use "personalfinance".

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Output Structure

The Actor pushes one dataset row per post returned. There is no wrapper object and no run-level summary row — the dataset is the result list.

Successful Output Format

{
  "id": "string",
  "title": "string",
  "text": "string",
  "author": "string",
  "subreddit": "string",
  "score": 0,
  "num_comments": 0,
  "created_utc": 0,
  "url": "string",
  "permalink": "string",
  "_query": "string"
}

Field Descriptions:

id • Type: string • Description: The Reddit post ID (base-36, e.g. 1c8x2fq). Stable — use it to deduplicate across repeated or scheduled runs.

title • Type: string • Description: The post title.

text • Type: string • Description: The post's self-text body. Empty ("") for link posts, image posts and other non-text submissions.

author • Type: string • Description: The Reddit username of the poster, without the u/ prefix.

subreddit • Type: string • Description: The subreddit the post lives in, without the r/ prefix. Useful when searching all of Reddit — it tells you which community each hit came from.

score • Type: number • Description: The post's score (upvotes minus downvotes) at the moment of the run. This is a live value and changes over time.

num_comments • Type: number • Description: The comment count at the moment of the run. Also a live value.

created_utc • Type: number • Description: The post's creation time as a UTC Unix timestamp, as published in the source data.

url • Type: string • Description: The post's content URL — the outbound link for link posts, or the Reddit thread URL for self-posts.

permalink • Type: string • Description: The full https://reddit.com/... link to the post's thread.

_query • Type: string • Description: A JSON string echoing back the search parameters the run actually used, including the applied defaults. Present on every row, success or error. Handy when you merge datasets from several runs and need to know which query produced which row.

Note on absent fields: fields the source data did not carry are omitted from the row entirely rather than set to null. Do not assume every key is present on every row — see Output Example 2. id, title and _query are the ones you can rely on in practice.

Note on status: successful post rows have no status field. Only error rows carry status: "error". Testing for row.status === "error" is the correct check; testing for status === "success" will match nothing.

You can download the dataset as JSON, CSV, Excel, HTML or XML from the Apify console, or fetch it through the Apify API.

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Output Examples

Example 1: Rich Result — Text Post with Full Data

{
  "id": "1c8x2fq",
  "title": "Why did EV prices drop so much this year?",
  "text": "Been watching the used market since January and the swings are wild. Three dealers near me have cut sticker twice...",
  "author": "range_anxiety_99",
  "subreddit": "electricvehicles",
  "score": 1842,
  "num_comments": 431,
  "created_utc": 1745012933,
  "url": "https://www.reddit.com/r/electricvehicles/comments/1c8x2fq/why_did_ev_prices_drop_so_much_this_year/",
  "permalink": "https://reddit.com/r/electricvehicles/comments/1c8x2fq/why_did_ev_prices_drop_so_much_this_year/",
  "_query": "{\"search\":\"electric vehicles\",\"filter\":\"posts\",\"timeFilter\":\"year\",\"sortType\":\"relevance\"}"
}

A self-post: every field populated, text carries the body, score and num_comments reflect the moment of the run.

Example 2: Link Post with No Body Text (Partial Data)

{
  "id": "1d0kq7m",
  "title": "EV sales grew 21% year over year, new registration data shows",
  "text": "",
  "author": "chartsandcharts",
  "subreddit": "electricvehicles",
  "score": 96,
  "num_comments": 8,
  "created_utc": 1747399201,
  "url": "https://example-news-site.com/ev-registrations-q2",
  "permalink": "https://reddit.com/r/electricvehicles/comments/1d0kq7m/ev_sales_grew_21_year_over_year_new_registration/",
  "_query": "{\"search\":\"electric vehicles\",\"filter\":\"posts\",\"timeFilter\":\"year\",\"sortType\":\"relevance\"}"
}

Link posts carry no self-text, so text is an empty string and url points off-site. This is a normal, fully successful result — not an error.

Example 3: Sparse Result — Fields Omitted

{
  "id": "1d33p8a",
  "title": "Charging network coverage map, updated",
  "text": "",
  "author": "gridmapper",
  "subreddit": "electricvehicles",
  "score": 14,
  "num_comments": 2,
  "_query": "{\"search\":\"electric vehicles\",\"filter\":\"posts\",\"timeFilter\":\"year\",\"sortType\":\"relevance\"}"
}

Here the source data carried no created_utc, url or permalink, so those keys are absent from the row rather than null. Write your integration to tolerate missing keys.

Example 4: No Results Found

When a search matches nothing, the run succeeds but pushes a single error row — the dataset is not empty:

{
  "status": "error",
  "_query": "{\"search\":\"asdkjhqwe zzz\",\"filter\":\"posts\",\"timeFilter\":\"hour\",\"sortType\":\"relevance\"}",
  "error": "No results were found for this input. You were not charged."
}

You are not charged. The most common causes are a timeFilter that is too narrow, an r/ prefix in subreddit, or a genuinely unmatched keyword.

Example 5: Service Busy (Rate Limited)

{
  "status": "error",
  "_query": "{\"search\":\"electric vehicles\",\"filter\":\"posts\",\"timeFilter\":\"year\",\"sortType\":\"relevance\"}",
  "error": "The service is busy right now — please retry in a moment. You were not charged."
}

Transient. Retry the run in a moment. You are not charged.

Example 6: Service Temporarily Unavailable

{
  "status": "error",
  "_query": "{\"search\":\"electric vehicles\",\"filter\":\"posts\",\"timeFilter\":\"year\",\"sortType\":\"relevance\"}",
  "error": "The data service is temporarily unavailable — please retry shortly. You were not charged."
}

The Actor already retried internally several times before emitting this. Retry the run shortly. You are not charged.

Example 7: Generic Failure

{
  "status": "error",
  "_query": "{\"search\":\"electric vehicles\",\"filter\":\"posts\",\"timeFilter\":\"year\",\"sortType\":\"relevance\"}",
  "error": "The request could not be completed right now. Please retry shortly. You were not charged."
}

The catch-all for anything unexpected. You are not charged. If it repeats for the same input, send us the run ID — see Support.

The four messages above are the complete set of error strings this Actor emits. They are fixed and self-authored; nothing from any internal service is ever passed through to you. Every error path pushes exactly one row, and every error path charges you nothing.

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Use Cases

For Marketers and Brand Teams

Brand and keyword monitoring: Reddit is where unfiltered opinion about your product actually lives, and most of it never reaches your support inbox. Search your brand, product names and competitor names on a schedule and get the mentions as rows.

Example Workflow:

1. Run with search: "<your brand>", timeFilter: "week", sortType: "new", limit: 100
2. Schedule the run daily in the Apify console
3. Deduplicate incoming rows on id against what you already stored
4. Sort new rows by score and num_comments to triage what is actually gaining traction
5. Open the permalink for anything that needs a response

For Product and Research Teams

Voice-of-customer mining: Pull long-tail complaints and feature requests in users' own words — the text field is the raw material for thematic coding.

Example Workflow:

1. Run several searches for the problem language your users use ("
2. Use timeFilter: "all" with sortType: "top" to find the canonical threads first
3. Then re-run with timeFilter: "month" and sortType: "new" for what is current
4. Export the dataset to CSV and tag title + text by theme
5. Weight themes by score and num_comments to separate loud from widespread

For Analysts and Researchers

Topic and sentiment datasets: Build a labeled corpus of public discussion on a topic, with engagement metrics already attached.

Example Workflow:

1. Define your keyword set and, if the topic has a home community, its subreddit
2. Run each keyword with timeFilter: "all", sortType: "top", limit: 100
3. Export as JSON and load into pandas or your notebook of choice
4. Use created_utc for time-series bucketing and score / num_comments as engagement weights
5. Keep _query alongside each row so the provenance of every data point stays traceable

For Sales and Lead Generation

Intent mining: Find people publicly asking for what you sell — "looking for a tool that...", "any recommendations for...".

Example Workflow:

1. Search intent phrases in your category, timeFilter: "week", sortType: "new"
2. Optionally restrict to the subreddit where your buyers gather
3. Filter rows by num_comments — unanswered threads are the warmest
4. Engage on the thread through the permalink, honestly and within the subreddit's rules

For Developers

Integration: Wire Reddit keyword search into your own product, alerting stack or CRM without touching Reddit's API, OAuth or rate limits.

Example Workflow:

1. Call the Actor through the Apify API with your query as input
2. Poll the run, then fetch the dataset items
3. Check row.status === "error" first and branch on it
4. Upsert the rest into your store keyed on id
5. Schedule it and treat each new id as an event

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Best Practices

Getting Good Results

• Start broad, then narrow. Run the keyword alone first. If you get too much noise, add subreddit; if you get too little, widen timeFilter.
• Match sortType to the job. relevance for discovery, new for monitoring, top for finding the canonical threads, comments for the most-discussed.
• timeFilter: "hour" is aggressive. On anything but a high-volume keyword it will often match nothing. Use day or week for monitoring.
• Never prefix subreddit with r/. It is the single most common cause of an empty result.
• Remember it searches posts, not comments. If your keyword tends to appear in replies rather than titles and bodies, search the broader topic term instead.

Error Handling

• Check status first — row.status === "error" identifies an error row. Success rows have no status field at all.
• Tolerate missing keys — created_utc, url and permalink can be absent from a row.
• Retry the transient ones — the busy and temporarily-unavailable messages are worth a retry; the "no results" message is not, since the input is what needs to change.
• Log run IDs — include the Apify run ID when contacting support.

Cost Control

• Set limit deliberately. It is your per-run spend cap; there is no reason to leave it at 100 while you are still tuning a query.
• Test with a small limit first. Run at limit: 5 to check that the query returns what you expect, then raise it.
• Empty and failed runs are free. Iterating on a query that returns nothing costs nothing.
• Deduplicate on id. Scheduled runs over overlapping time windows will return posts you already have — and yes, you pay for them again, so keep windows tight.

Data Usage

• Scores and comment counts are snapshots taken at run time. Re-run if you need current engagement numbers.
• Respect Reddit's rules and each subreddit's rules if you act on what you find.
• Handle personal data lawfully — usernames are personal data under GDPR and similar regimes.

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Cost, Performance, and Limits

Pricing

This Actor uses pay per result. You are charged $0.0058 per post returned — the post-returned event fires once for each post pushed to the dataset.

You are charged nothing for:

• Runs that find no matching posts
• Runs that hit a rate limit or a temporary service failure
• Any error row of any kind

No monthly subscription, no minimums, no charge for a run that gives you nothing.

Performance

• Instant by design. A run issues a single search request and returns — typically seconds, not minutes. No browser, no crawl.
• Automatic retries. Transient failures are retried internally, with backoff, before the run reports a failure to you. That work is invisible and costs you nothing extra.
• Default resources are sufficient. The Actor is not CPU- or memory-bound; leave the defaults.

Limits

• 1–100 posts per run — set by limit, default 25.
• One search request per run. The Actor does not paginate: a run returns at most what a single search response contains, capped by your limit. It is not a bulk historical archive tool.
• Posts only — not comments, not users, not subreddit listings.
• One query per run. To search several keywords, run the Actor several times (schedule them, or drive it via the Apify API).
• Public content only — no private subreddits, no deleted posts, nothing behind a login.
• Live values — score and num_comments are snapshots at run time, not stable identifiers.

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Data Sources and Legality

This Actor accesses only publicly available information on Reddit — posts that their authors chose to publish publicly and that any logged-out visitor can read. It does not access private subreddits, direct messages, deleted content, or anything requiring authentication. It does not attempt to circumvent access controls.

Your responsibilities:

• You are responsible for complying with applicable laws — including GDPR, CCPA and other data-protection regimes — when you collect, store or process the results.
• Usernames and post content may constitute personal data. Have a lawful basis before you process them, and honor deletion requests.
• Respect Reddit's terms of service and each subreddit's rules, particularly if you engage with the threads you find.
• Reddit content is authored by its posters and remains theirs. Republishing it may require attribution or permission.

This Actor is not affiliated with, endorsed by, or sponsored by Reddit. Nothing here is legal advice; if your use case is sensitive, get advice that is.

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Contact & Support

Questions? Need Help? We're Here for You!

For any questions, technical support, feature requests, or general inquiries about the Reddit Keyword Search Scraper, please reach out:

Email: contact@endspec.net

Response Time: We respond within 24 hours during business days.

What to Include in Your Inquiry:

• Your question or issue description
• Actor run ID (if applicable)
• The exact input JSON you used
• The error message or row you received, if any
• What you expected instead

We are committed to providing excellent support and helping you get the most out of this Actor — whether you are integrating it into a workflow, troubleshooting a query that returns nothing, or exploring a new use case.

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Frequently Asked Questions

Q: Do I need a Reddit account or an official Reddit API key? A: No. There is nothing to authenticate, register or configure. Provide a search keyword and run the Actor.

Q: Will empty or failed runs cost me anything? A: No. You are charged only per post actually returned. A search that matches nothing, or a run that hits a transient failure, costs you nothing.

Q: My search returned an error row saying "No results were found for this input" — is the Actor broken? A: Almost certainly not. That message means the search ran fine and matched zero posts. Check three things, in order: an r/ prefix in subreddit (remove it), a timeFilter that is too narrow (widen it), and the keyword itself (broaden it).

Q: Why is the dataset not simply empty when there are no results? A: By design — the run tells you why you got nothing rather than leaving you with a silent empty dataset. Zero matches pushes one row with status: "error" and the "no results" message. You are not charged for it.

Q: Does it search Reddit comments? A: No. Results are posts only — the keyword is matched against titles and self-text. A keyword appearing only inside a comment thread will not match.

Q: Can I get more than 100 posts in one run? A: No — limit caps at 100, and a run issues a single search request. For broader coverage, split the work: run several narrower queries (by subreddit, by time window, by keyword variant) and combine the datasets, deduplicating on id.

Q: Why did I get fewer posts than my limit? A: limit is a maximum, not a target. Your query simply matched fewer posts. You are charged only for what you received.

Q: How do I restrict the search to one subreddit? A: Set subreddit to the plain community name with no r/ prefix — "technology", not "r/technology". Leave it empty to search all of Reddit.

Q: How is this different from the Reddit Subreddit Scraper? A: This Actor is keyword-driven: you give it a search query and it finds matching posts anywhere on Reddit (or inside one subreddit you name). The Reddit Subreddit Scraper is feed-driven: you give it a subreddit and it exports that community's new/hot/top/rising posts with no keyword at all. Use this one to find mentions of a topic; use that one to follow a community.

Q: How fresh is the data? A: It is fetched live at run time. score and num_comments are snapshots from the moment of the run and will drift afterwards.

Q: Can I get historical posts? A: Set timeFilter: "all" to search Reddit's full history. Note that a single run still returns at most limit posts from one search — combine sortType: "top" with timeFilter: "all" to get the most significant historical threads rather than an exhaustive archive.

Q: Why do some rows lack created_utc, url or permalink? A: Those fields are omitted when the source data does not carry them. Absent keys are normal; write your integration to tolerate them.

Q: What is the _query field for? A: It echoes back the search parameters the run actually used, defaults included. It is on every row, including error rows, so that merged datasets stay traceable to the query that produced them.

Q: Can I run this Actor commercially? A: Yes. All data returned is publicly available. You remain responsible for complying with applicable law and with Reddit's terms.

Q: Can I schedule it? A: Yes. Use Apify's scheduler for recurring monitoring. Pair a short timeFilter with sortType: "new" and deduplicate on id.

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Related Actors

• Reddit Subreddit Scraper – Export the new, hot, top or rising posts from any public subreddit, no keyword needed.
• YouTube Instant Email Scraper – Find publicly listed contact emails for YouTube channels.
• LinkedIn Instant Profile Search – Search LinkedIn profiles by name, job title or company.

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Last Updated: July 2026