Quora Monitor: Up to 1,000 Free Results a Month (2026)

Each dataset record carries 20 fields under identity, event, and text, letting you track public Quora questions, answers, profiles, topics, and spaces across recurring runs. The Actor compares each observation against past state to isolate new, modified, or unchanged public items without false deletion alerts. Output items cost $5.00 per 1,000 results on the free plan, which covers up to 1,000 results of this Actor per month. This tool serves community managers, analysts, and content teams auditing visible edits on specific Quora pages; it is not for anyone needing gated Quora+ text or private contact details, which the records do not include.

Try it: open Quora Monitor on Apify, sign in on the free plan and run the prefilled example.

Can you try Quora Monitor before paying?

Yes. Apify's free plan includes $5.00 of prepaid usage every month and asks for no credit card. At $0.005 per result, that covers up to 1,000 results of Quora Monitor a month, before run-start charges and platform usage.

Quora Monitor was last updated on 2026-09-11. It is one of 1,725 Actors CrawlerBros publishes on Apify, which together have 692,561 lifetime public runs and an average rating of 4.63 out of 5 across 416 reviews.

What does it cost to run Quora Monitor?

Each result costs $0.005 on Apify's free plan, which is $5.00 per 1,000 results. Apify also bills the platform usage each run consumes, at the rates of your Apify plan, on top of these charges.

Charges apply per result written to your dataset, making maxResults and maxFeedItems the dominant cost drivers on any run. The most economical approach is to run a single target URL with maxResults set to 1 to verify your historyName baseline before expanding to large feeds.

How do you run Quora Monitor from the API?

None of its 27 controls is strictly required, so the defaults below produce a valid run on their own. Nothing in the payload below is illustrative. Those are the schema's prefilled defaults for Quora Monitor, so the request works once your token is in place.

Call the synchronous endpoint to start a run and receive dataset items in one request:

curl -X POST "https://api.apify.com/v2/acts/crawlerbros~quora-monitor-scraper/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"directUrls":["https://www.quora.com/What-is-Python-primarily-used-for"]}'

The same run from Python, using the official client:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")

run_input = {
  "directUrls": [
    "https://www.quora.com/What-is-Python-primarily-used-for"
  ]
}

run = client.actor("crawlerbros~quora-monitor-scraper").call(run_input=run_input)

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

And from Node.js:

import { ApifyClient } from 'apify-client'

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' })

const input = {
  "directUrls": [
    "https://www.quora.com/What-is-Python-primarily-used-for"
  ]
}

const run = await client.actor('crawlerbros~quora-monitor-scraper').call(input)
const { items } = await client.dataset(run.defaultDatasetId).listItems()
console.log(items)

Because the call is synchronous, your client waits for the whole run. Keep it for exploration. For scheduled work, start the run without waiting and collect the dataset afterwards, so network trouble costs you a retry rather than the results.

Which Quora Monitor inputs matter, and which can you skip?

The main controls are directUrls to specify the target links and historyName to anchor comparisons across recurring runs. Most practitioners should leave cookies blank and reachMode on standard, as public pages are queried anonymously first.

• directUrls (array): Public Space, question, answer, profile, topic, or post URLs.
• searchQueries (array): Terms whose public discovery results should be checked.
• includeFeed (boolean): Check visible feed items for changes. Default: true.
• scrapeDepth (string): Summary only, or summary plus visible feed and contributors. Default: "detail".
• feedTab (string): Choose which visible Space section to monitor. Default: "all".
• includeContributors (boolean): Check visible Space contributors for changes. Default: false.
• maxFeedItems (integer): Maximum visible feed items checked in each Space. Default: 50.
• maxContributors (integer): Maximum visible contributors checked in each Space. Default: 50.
• maxFeedQuestionExpansions (integer): When Scrape Depth is detail, bounded number of question-type feed items to open and expand into full question fields (question_id, question_answer_count, question_view_count, question_details, question_created_at, question_updated_at). Zero keeps the feed-digest-only behavior. Default: 0.
• includeFeedText (boolean): Include visible feed text evidence. Default: true.
• includeMedia (boolean): Include visible media URLs when present. Default: false.
• includeOutboundLinks (boolean): Include bounded outbound links from feed cards. Default: false.

The other 15 controls, with their defaults, are listed in the input schema on Quora Monitor on Apify.

Fixed-choice controls: scrapeDepth accepts overview (Summary only), detail (Detailed changes); feedTab accepts all (All visible sections), posts, questions, top (Top content), unanswered (Unanswered questions), about, rules.

What does Quora Monitor return?

The output records provide before-and-after change diffs, visible text, author handles, and engagement counts. They do not contain private email addresses, hidden phone numbers, or paywalled Quora+ answers.

Identity, event, and text

• recordType, id, url, title, text, collectedAt, accessState, details
• eventType, changeType, changes, questionText, answerText, postText, commentText, profileBio, authorBio, topicDescription, spaceDescription, resultSnippet

Watched content

• questionId, questionUrl, questionTitle, questionPublishedAt, questionUpdatedAt, questionLastAnsweredAt, isUnanswered, topics, relatedQuestions
• answerId, answerUrl, answerPostedAt, answerCreatedAt, answerRelativeAge, answerUpdatedAt, answerRank, answerVisibility, answerTextCompleteness, answerAccessOption, isAiAnswer, isTopAnswer, isTruncated
• authorName, authorUrl, authorId, authorHandle, authorCredentials, authorImageUrl, authorIsVerified, username

Counts, media, and relationships

• answerCount, followerCount, followingCount, questionCount, postCount, memberCount, contributorCount, viewCount, upvotes, commentsCount, sharesCount, commentReplyCount, reactionCount, totalAnswerViews, totalContentViews, answerToViewRatio, followToAnswerRatio, answersCollected, answersLimitReached
• images, videos, externalLinks, textCompleteness, searchType, searchRank, searchTitle, searchSnippet, isPromoted
• fromUrl, toUrl, relationshipType

These are the documented fields. Optional ones can be empty on a given record, so measure how often each field your deliverable depends on is populated across a real sample before automating the handoff.

How do you build the workflow end to end?

Open Quora Monitor and work through these in order. Each step ends with something to check, so a bad configuration surfaces on a small run rather than a scheduled one.

1. Populate directUrls with your target public question or Space URL.
2. Set historyName to a fixed string so future scheduled runs bind to the same comparison baseline.
3. Leave scrapeDepth at detail if you need full Space feed items and contributor tracking, or select overview for top-level metadata.
4. Choose field_values for changeDetail to inspect both prior and current values whenever an edit occurs.
5. Run the Actor once to write the initial baseline observation into the dataset with eventType set to initial_snapshot.
6. Verify the first record contains a populated accessState and valid identity fields before creating an automated schedule.
7. Create an Apify schedule using the identical historyName and adjust onlyNewItems to true if you only wish to export deltas.

How do you apply it? Three worked playbooks

These are Quora Monitor's own documented use cases, each worked through as an operating pattern rather than a description.

Use case 1: Scheduled alerts

Outcome: Scheduled alerts: detect new or changed public Quora content.

Configure: Set directUrls to ["https://www.quora.com/What-is-Python-primarily-used-for"], historyName to "python-alerts", onlyNewItems to true, includeUnchanged to false, and changeDetail to "hash_and_summary".

Working method: Execute an initial run to store the baseline snapshot under the chosen historyName. Schedule the Actor to run on a recurring timer with identical settings so that only novel public posts or answers trigger dataset writes.

Deliverable: A periodic dataset containing exclusively new question and answer additions with valid answerId and authorName fields.

Stop condition: The Actor emits records with empty questionText or missing answerId across consecutive scheduled executions.

Use case 2: Community monitoring

Outcome: Community monitoring: watch Space feeds, Topics, rules, and contributors.

Configure: Set directUrls to ["https://cryptocurrency.quora.com/"], historyName to "crypto-space-audit", includeFeed to true, feedTab to "questions", maxFeedItems to 50, and includeContributors to true.

Working method: Start with a single Space URL to capture member rosters and published guidelines. Run recurring checks weekly to compare changes across contributorCount, memberCount, and rules text.

Deliverable: A structured export logging shifts in contributor lists, participation rules, and Space topic tags over time.

Stop condition: Repeated runs return zero feed items while manual browser inspection confirms public activity is visible.

Use case 3: Content operations

Outcome: Content operations: identify when a public question or answer changes.

Configure: Set directUrls to ["https://www.quora.com/What-are-the-major-differences-between-NAFTA-and-TPP"], historyName to "trade-content-ops", includeUnchanged to true, changeDetail to "field_values", and scrapeDepth to "detail".

Working method: Capture the initial text snapshot of your primary target answer. Trigger the monitor across scheduled intervals to catch text revisions, comparing before and after values under the changes object.

Deliverable: A change log containing before and after field values for answerText and answerUpdatedAt.

Stop condition: The returned recordType is an access error instead of monitor_event, indicating the target page was not served.

What breaks, and how do you design around it?

When monitoring high-volume Space feeds, the default ceiling of 50 visible items can miss fast-moving posts if checks are spaced too far apart. Rather than expanding maxFeedItems to huge sizes, schedule the runs more frequently so smaller batches capture every increment. When a page fails to load, the Actor flags an access event instead of generating a false removal, keeping your baseline intact.

When should you not use Quora Monitor?

Do not use this Actor if your objective is broad discovery or initial keyword harvesting across Quora. If you need to search keywords and retrieve matching questions or author statistics from scratch, use Quora Search Scraper instead. Similarly, if you want a one-off bulk export of user profiles or Space posts without delta tracking or historical state storage, use Quora Scraper. This monitor is designed strictly for recurring differential tracking of established public URLs.

What should you check before trusting the output?

• Verify that accessState equals public on your initial baseline run before relying on subsequent diffs.
• Confirm that changes contains expected property keys whenever changeType reports an update.
• Check that questionId or answerId is populated to confirm content cards rendered properly.
• Halt execution if includeAccessIssues is true and records report unavailable sources repeatedly across consecutive runs.

None of this proves a record is correct. It gives a scheduled Quora Monitor run defined points where it should stop instead of quietly passing bad data downstream.

Frequently asked questions

How does historyName maintain state between runs?

Supplying the same historyName on consecutive runs causes the Actor to pull its previous snapshot from Apify storage. The Actor compares incoming visible fields against that baseline, reporting new additions or edits while preserving your monitoring timeline.

What happens if Quora blocks a page during an observation?

A blocked or unavailable page is marked separately rather than treated as removed or unchanged. This prevents temporary network barriers from contaminating your baseline with false deletion records.

Are browser cookies required to run this monitor?

No cookies are required. The Actor queries public Quora endpoints anonymously by default. Cookies are strictly optional and only grant access to content already visible to that specific authorized account session.

What is the difference between onlyNewItems and includeUnchanged?

Setting onlyNewItems to true suppresses records that have already been recorded in previous baseline snapshots. Setting includeUnchanged to false drops records where the target page was successfully reached but no public text or metric changed.

What does running this Actor cost on Apify's free plan?

Usage costs $5.00 per 1,000 results on the free plan, which equals $0.005 per result written to your dataset. Apify's monthly prepaid allowance covers up to 1,000 results of this Actor each month without requiring a credit card.

Where to go next

When you are ready to run it, open Quora Monitor on Apify; the free plan covers up to 1,000 results a month.

Start with the Quora Monitor Actor page for the current input schema, pricing tier, and run history.

Other Actors we maintain for related data:

• Quora Scraper: Scrape Quora questions, answers, user profiles, topics, and spaces.
• Quora Search Scraper: Search Quora by keywords and extract questions, answers, author info, upvotes, and engagement metrics.
• DuckDuckGo Instant Answer Scraper: Scrape DuckDuckGo Instant Answers for any search query.
• LinkedIn Profile Posts Scraper: Scrape all posts, articles, and reposts from any LinkedIn profile's activity feed.
• TeamBlind Scraper: Scrape posts, comments, topic feeds, and company feeds from TeamBlind, the anonymous workplace community for tech employees.
• Our World in Data Scraper: Scrape Our World in Data (ourworldindata.org) - browse articles by topic or keyword, fetch chart data (CSV) by slug, or explore country profiles.
• LinkedIn Post Scraper: Scrape posts from any LinkedIn personal profile activity feed.

Related guides:

• Stack Exchange Scraper Use Cases

Resources

• Actor documentation, input schema, and pricing: verified against the published Actor on 2026-09-29.

• Actor last updated by its maintainers on 2026-09-11.

• Run outcome figures cover the 30 day public window ending 2026-09-29.

• Quora Monitor on Apify