Quora Search Scraper

🔎 Search public Quora content by keyword or URL

Quora Search Scraper helps content researchers, SEO teams, and market researchers find public Quora pages. Search with keywords or open public URLs, then save questions, visible answers, profiles, topics, spaces, and posts with source links and public counts. Review or export the structured data without a Quora login.

• Collect public questions, topic labels, answer counts, and source URLs with Quora Question Research.
• Export visible answer text, authors, credentials, dates, and engagement counts with Quora Answer Scraping.
• Study terms and themes in public questions, answers, and posts with Quora Content Research.
• Find indexed public Quora pages for a keyword and record discovery rank with Quora Keyword Research.
• Re-run keyword searches with a date range to track public topic activity with Quora Topic Monitoring.
• Collect public profile names, descriptions, images, and activity counts with Quora Profile Scraping.
• Turn public Quora page URL lists into structured data with Quora URL Scraping.

The Actor uses public pages and does not collect private, login-only, restricted, or Quora+ paywalled content.

📦 Quora page rows

Each saved row is one public Quora page. The Actor saves the first eligible match for a source item. If another keyword, URL, or other submitted value finds that item later, the later match is skipped and does not rewrite the saved row. The matchedInput field shows the submitted value that first caused the row to be saved.

Question rows keep visible answers in an answers array. Profile, topic, space, and post rows use page-specific fields. A field appears only when Quora shows it on a public page, so missing facts are left out.

🚀 Run Quora searches and page URLs

1. Add keywords or public Quora URLs to Keywords or Quora URLs.
2. Choose the page type for keyword discovery.
3. Choose a date range when you want to filter keyword discovery.
4. Set answer options and the whole-run result limit.
5. Run the Actor and open the dataset.

You can mix keywords and direct URLs in one run. The page type and date range affect keyword values only. Direct public URLs are opened as given. Leave the result limit empty to return all available results until the source is exhausted.

⚙️ Input

Public input example

This example is copied from a successful current-beta keyword run:

{
  "targets": [
    "machine learning careers"
  ],
  "searchType": "question",
  "dateRange": "any",
  "answerDepth": "all",
  "answerOrder": "relevance",
  "globalOrder": "relevance",
  "maxResults": 2
}

Input fields

Field	Type	What it does
targets	array of strings (required)	Adds one or more keywords, public Quora page URLs, or both. URLs can point to questions, profiles, topics, spaces, posts, or Quora search pages.
searchType	string (required)	Chooses the public page type for keyword discovery: question, profile, topic, space, post, or all. Direct URLs are opened as given.
dateRange	string	Sets a date window for pages found through keywords when Quora shows a usable source date: any, day, week, month, or year. Direct URLs are not filtered by it.
topicFilter	array of strings	For keyword-discovered questions, keeps pages that show at least one listed public topic label. It does not filter direct URLs or other page types. An empty list keeps every matching page.
answerDepth	string	Chooses top visible answers or all visible answers for each question.
minAnswerUpvotes	integer	Keeps only answers with at least this many public upvotes. An empty value keeps all visible answers, and a question stays even if no answer meets the threshold.
answerOrder	string	Orders answers inside each question by relevance, recency, or upvotes.
globalOrder	string	Orders saved rows across the run by relevance, recency, or upvotes when Quora shows the needed public date or upvote data.
maxResults	integer	Sets the whole-run limit for saved rows. Leave it empty to return all available results until the source is exhausted.

🧾 Output

Rows use one of five shapes. The tables below list every field in the public dataset schema. Fields that Quora does not show are omitted. Dotted names describe fields inside an object or an array item. Each example is a complete genuine row from a current-beta run.

Question row

Field	Type	What it does
contentType	string	Identifies this row as a question.
matchedInput	string	Shows the keyword or Quora URL whose first eligible match saved this row.
discoveryRank	integer	Shows the page position for the submitted keyword when available.
title	string	Gives the question title.
url	string	Gives the canonical public Quora question URL.
questionId	integer	Gives the Quora question ID.
topics	array of strings	Lists visible topic labels on the question.
answerCount	integer	Gives the visible answer count.
followerCount	integer	Gives the visible follower count.
answers	array of objects	Holds the visible answers collected with the question.
answers[].answerId	integer	Gives the Quora answer ID.
answers[].rank	integer	Gives the answer position in the loaded public list.
answers[].url	string	Gives the canonical public answer URL.
answers[].text	string	Gives the full visible answer text.
answers[].author	object	Holds visible answer-author details.
answers[].author.name	string	Gives the public author name.
answers[].author.url	string	Gives the public author profile URL.
answers[].author.credential	string	Gives the public author credential when shown.
answers[].author.imageUrl	string	Gives the public author image URL when shown.
answers[].author.isAi	boolean	Says whether Quora identifies the author as an AI account.
answers[].createdAt	date-time string	Gives the answer creation time when shown.
answers[].updatedAt	date-time string	Gives the answer update time when shown.
answers[].upvoteCount	integer	Gives the public answer upvote count.
answers[].commentCount	integer	Gives the public answer comment count.
answers[].shareCount	integer	Gives the public answer share count.
answers[].viewCount	integer	Gives the public answer view count.
answers[].mediaUrls	array of strings	Lists public media URLs attached to the answer.

Example question row

This complete row was saved by a keyword search for neural networks:

{
  "contentType": "question",
  "matchedInput": "neural networks",
  "discoveryRank": 2,
  "title": "What are neural networks in machine learning?",
  "url": "https://www.quora.com/What-are-neural-networks-in-machine-learning",
  "questionId": 31526547,
  "topics": [
    "Computer Science",
    "Artificial Intelligence",
    "Algorithms",
    "Neural Networks (general)",
    "Data Science",
    "Machine Learning Theory",
    "Neural Computation",
    "Machine Learning",
    "Artificial Intelligence Neural Networks",
    "Deep Learning"
  ],
  "answerCount": 2,
  "answers": [
    {
      "answerId": 173195182,
      "rank": 1,
      "url": "https://www.quora.com/What-is-CNN-in-machine-learning/answer/Muhammad-Asem",
      "text": "CNN “Convolutional Neural Network” is more commonly listed under deep learning algorithms which is a subset of machine learning and AI.\nConvolution means, convolving/applying a kernel/filter of nxn dimension on a selected pixel and its surroundings, then moving the same kernel to the next pixel and its surrounding and so on, to asses each pixel.\nMainly, CNN is used with images to extract features. Although features, shapes and patterns can be detected directly using multilayer sequential neural networks, CNN is more accurate.\nCNN applies filters to each pixel of the image to examine the feature type which this pixel belongs to, whether it is a line, half circle, curve,etc.\nPixels which gives a high score after it is convolved with a straight line filter, most probably belongs to a straight line.\nThe above figure shows a kernel of size 3x3 that gives a maximum value for detecting a diagonal. Image source :Deep learning Udacity Nanodegree .\nFilter/kernel size determines the size around the pixel to consider during feature examination.\nDetecting a square is done by detecting its edges first, “straight lines” then form a complete understanding of the shape .\nHorizontal edge with another vertical one, form a half square, half square with another half, signals a complete square. This process is done over multiple CNN layers, each layer has its own function till the assembly.\nThe same happens with circles as shown\nA circle is detected with steps, the upper left curve with a upper right ..etc. results in a complete circle understanding as shown in the above figure. See more in this youtube channel.\nThis is also used for detecting the handwritten letters. Each set of layers can detect a feature in the image combining different features results in different shapes of numbers.\nIn this figure, both numbers, 8 and 9 has an upper loop, while 9 has a lower straight line, 8 has a lower loop. A layer(s) in this network is dedicated for loop detection another one for vertical line detection. Analysing the features within the input will lead to classify the number inside the image.\nThe beauty is that, the values of these filters are determined by training the network not by your selection :).",
      "author": {
        "name": "Muhammad Asem",
        "url": "https://www.quora.com/profile/Muhammad-Asem",
        "credential": "Teaching and Research Assistant  at Zewail City of Science and Technology",
        "imageUrl": "https://qph.cf2.quoracdn.net/main-thumb-198009206-200-dzflalenebxudsljxlheojunarhqyqon.jpeg",
        "isAi": false
      },
      "createdAt": "2019-10-10T15:56:18.953Z",
      "upvoteCount": 59,
      "commentCount": 0,
      "shareCount": 2,
      "viewCount": 3788,
      "mediaUrls": [
        "https://qph.cf2.quoracdn.net/main-qimg-aa5548f3c257c51eae0215be4437c7e1",
        "https://qph.cf2.quoracdn.net/main-qimg-b467be395f3d892a8f29e5b702b495c1",
        "https://qph.cf2.quoracdn.net/main-qimg-9d0b83622b3e35a7b01871f0d38fa330-pjlq",
        "https://qph.cf2.quoracdn.net/main-qimg-168455876910cfd7363ec8a7e6d4bbf7",
        "https://qph.cf2.quoracdn.net/main-qimg-cef864018101a663722c89b1bb51ef4d",
        "https://qph.cf2.quoracdn.net/main-qimg-1790f87e362066479cdc16a81467138e",
        "https://qph.cf2.quoracdn.net/main-qimg-f7faf5b380a41351bb7195106b67efe0-pjlq"
      ]
    },
    {
      "answerId": 301270233,
      "rank": 2,
      "url": "https://www.quora.com/What-are-neural-networks-in-machine-learning/answer/Harsh-Gupta-2712",
      "text": "Neural networks are made up of layers of neurons. The first layer, the input layer, receives values from other sources, such as an image or video feed. The next layers are hidden layers which take their inputs from either the previous nodes or the output nodes of the network and then process those values into a usable form for either controlling a robot's movements (e.g. controlling a robot arm to pick up an object) or classifying a certain input into one of a few predefined categories. The final layer, the output layer, is responsible for producing values based on the input collected from the hidden layers. Those outputs are sent back through the network and maybe processed again by other nodes in later layers until they reach their final destination, in the form of a very complex activation map (a vector) which represents a type of value.\nThese nodes often process their values through mathematical functions, such as logistic regression and sigmoid functions. These various methods are designed to help the network learn how to produce outputs based on different inputs without having an external trainer constantly correcting errors when mistakes are made. This is known as unsupervised learning. To achieve supervised learning, one could train the network by having someone (or something) provide labels for certain inputs. The network can then compare its output from these inputs with labels provided by a human expert or another neural network that has already been trained on these specific data sets and adjust accordingly so that it produces correct answers for future inputs.\nThe key to understanding how neural networks learn is understanding that what they are learning is the relationship between the values of the input nodes and their corresponding outputs.",
      "author": {
        "name": "Harsh Gupta",
        "url": "https://www.quora.com/profile/Harsh-Gupta-2712",
        "credential": "Make $$$ listening to b2b sales pitches on fozzie.io",
        "imageUrl": "https://qph.cf2.quoracdn.net/main-thumb-1150084439-200-bsvjfaduxzdksctdicufsdnlnadhlatn.jpeg",
        "isAi": false
      },
      "createdAt": "2021-08-11T13:09:08.234Z",
      "upvoteCount": 13,
      "commentCount": 0,
      "shareCount": 3,
      "viewCount": 2027,
      "mediaUrls": []
    }
  ]
}

Profile row

Field	Type	What it does
contentType	string	Identifies this row as a profile.
matchedInput	string	Shows the keyword or Quora URL whose first eligible match saved this row.
discoveryRank	integer	Shows the page position for the submitted keyword when available.
title	string	Gives the public profile name.
url	string	Gives the canonical public Quora profile URL.
profileId	integer	Gives the Quora profile ID.
description	string	Gives the public profile description or credential when shown.
imageUrl	string	Gives the public profile image URL when shown.
followerCount	integer	Gives the visible follower count.
followingCount	integer	Gives the visible following count.
answerCount	integer	Gives the visible answer count for the profile.
postCount	integer	Gives the visible post count for the profile.

Example profile row

{
  "contentType": "profile",
  "matchedInput": "https://www.quora.com/profile/Mike-West-99",
  "title": "Mike West",
  "url": "https://www.quora.com/profile/Mike-West-99",
  "profileId": 263407715,
  "imageUrl": "https://qph.cf2.quoracdn.net/main-thumb-263407715-200-mirkpaqqqfbiatlzukudohupoachleiq.jpeg",
  "followerCount": 20335,
  "followingCount": 15
}

Topic row

Field	Type	What it does
contentType	string	Identifies this row as a topic.
matchedInput	string	Shows the keyword or Quora URL whose first eligible match saved this row.
discoveryRank	integer	Shows the page position for the submitted keyword when available.
title	string	Gives the public topic name.
url	string	Gives the canonical public Quora topic URL.
topicId	integer	Gives the Quora topic ID.
description	string	Gives the public topic description when shown.
imageUrl	string	Gives the public topic image URL when shown.
followerCount	integer	Gives the visible follower count.
questionCount	integer	Gives the visible question count.
topics	array of strings	Lists visible related topic labels.

Example topic row

{
  "contentType": "topic",
  "matchedInput": "https://www.quora.com/topic/Jobs-and-Careers-in-Machine-Learning",
  "title": "Jobs and Careers in Machine Learning",
  "url": "https://www.quora.com/topic/Jobs-and-Careers-in-Machine-Learning",
  "topicId": 2134490,
  "imageUrl": "https://qph.cf2.quoracdn.net/main-thumb-t-948-100-kfdrdbxmzmijrndlcvxdftbghuzsjpmc.jpeg",
  "followerCount": 125,
  "topics": []
}

Space row

Field	Type	What it does
contentType	string	Identifies this row as a space.
matchedInput	string	Shows the keyword or Quora URL whose first eligible match saved this row.
discoveryRank	integer	Shows the page position for the submitted keyword when available.
title	string	Gives the public space name.
url	string	Gives the canonical public Quora space URL.
spaceId	integer	Gives the Quora space ID.
description	string	Gives the public space description when shown.
imageUrl	string	Gives the public space image URL when shown.
followerCount	integer	Gives the visible follower count.
memberCount	integer	Gives the visible member count.
contributorCount	integer	Gives the visible contributor count.
postCount	integer	Gives the visible post count.

Example space row

{
  "contentType": "space",
  "matchedInput": "https://theenglishlab.quora.com",
  "title": "The English Lab",
  "url": "https://theenglishlab.quora.com",
  "spaceId": 1577079,
  "description": "It relates to English Grammar and vocabulary. ",
  "imageUrl": "https://qph.cf2.quoracdn.net/main-thumb-ti-1577079-100-yhtcovazpijvdshydmsvbsrugkgndhon.jpeg",
  "followerCount": 69305,
  "memberCount": 69423,
  "contributorCount": 108,
  "postCount": 23298
}

Post row

Field	Type	What it does
contentType	string	Identifies this row as a post.
matchedInput	string	Shows the keyword or Quora URL whose first eligible match saved this row.
discoveryRank	integer	Shows the page position for the submitted keyword when available.
title	string	Gives the visible post title or a concise title from its text.
url	string	Gives the canonical public Quora post URL.
postId	integer	Gives the Quora post ID.
text	string	Gives the full visible post text.
author	object	Holds visible post-author details.
author.name	string	Gives the public author name.
author.url	string	Gives the public author profile URL.
author.credential	string	Gives the public author credential when shown.
author.imageUrl	string	Gives the public author image URL when shown.
associatedEntity	object	Holds the public profile, topic, or space linked to the post.
associatedEntity.type	string	Identifies the linked entity as a profile, topic, or space.
associatedEntity.name	string	Gives the linked entity name.
associatedEntity.url	string	Gives the linked entity URL.
associatedEntity.description	string	Gives the linked entity description when shown.
associatedEntity.imageUrl	string	Gives the linked entity image URL when shown.
createdAt	date-time string	Gives the post creation time when shown.
updatedAt	date-time string	Gives the post update time when shown.
upvoteCount	integer	Gives the public post upvote count.
commentCount	integer	Gives the public post comment count.
shareCount	integer	Gives the public post share count.
viewCount	integer	Gives the public post view count.
mediaUrls	array of strings	Lists public media URLs embedded in the post.

Example post row

{
  "contentType": "post",
  "matchedInput": "https://apdaga.quora.com/Coursera-Machine-Learning-Week-5-Assignment-Solution-Andrew-NG-APDaga-DumpBox",
  "title": "Coursera: Machine Learning (Week 5) [Assignment Solution] - Andrew NG | APDaga | DumpBox",
  "url": "https://apdaga.quora.com/Coursera-Machine-Learning-Week-5-Assignment-Solution-Andrew-NG-APDaga-DumpBox",
  "postId": 7056437,
  "text": "Coursera: Machine Learning (Week 5) [Assignment Solution] - Andrew NG\n▸ Back-propagation algorithm for neural networks to the task of hand-written digit recognition.\nIt consist of the following files:\nex4.m - Octave/MATLAB script that steps you through the exercise\nex4data1.mat - Training set of hand-written digits\nex4weights.mat - Neural network parameters for exercise 4\nsubmit.m - Submission script that sends your solutions to our servers\ndisplayData.m - Function to help visualize the dataset\nfmincg.m - Function minimization routine (similar to fminunc)\nsigmoid.m - Sigmoid function\ncomputeNumericalGradient.m - Numerically compute gradients\ncheckNNGradients.m - Function to help check your gradients\ndebugInitializeWeights.m - Function for initializing weights\npredict.m - Neural network prediction function\n[*] sigmoidGradient.m - Compute the gradient of the sigmoid function\n[*] randInitializeWeights.m - Randomly initialize weights\n[*] nnCostFunction.m - Neural network cost function\nVideo - YouTube videos featuring Free IOT/ML tutorials\n* indicates files you will need to complete view more…\nThanks & Regards,\n- Akshay P Daga\nDISCLAIMER:\nThese solutions are for reference only.\n> It is recommended that you should solve the assignments by yourself honestly then only it makes sense to complete the course.\n> But, In case you stuck in between, feel free to refer to the solutions provided by me.\nNOTE:\nDon't just copy paste the code for the sake of completion.\nEven if you copy the code, make sure you understand the code first.",
  "author": {
    "name": "Akshay Daga",
    "url": "https://www.quora.com/profile/Akshay-Daga-1",
    "credential": "System Engineer at Tata Consultancy Services (2016-present)"
  },
  "associatedEntity": {
    "type": "space",
    "name": "APDaga DumpBox",
    "url": "https://apdaga.quora.com",
    "description": "The Thirst for learning... The knowledge sharing place...",
    "imageUrl": "https://qph.cf2.quoracdn.net/main-thumb-ti-639506-100-gduypanxaghbzyvlfzomtnatyyhhurdi.jpeg"
  },
  "createdAt": "2019-03-31T19:22:31.317Z",
  "upvoteCount": 0,
  "commentCount": 0,
  "shareCount": 0,
  "viewCount": 787,
  "mediaUrls": []
}

Dataset link

The results link in the Output tab opens the default overview view of the saved dataset. You can also read the dataset through the Apify API or export it as JSON, CSV, Excel, XML, RSS, or HTML.

💳 Pricing

This Actor uses pay-per-event pricing. The quora-result event is charged once when a public question, profile, topic, space, or post is saved. A run with no saved page does not create this result event. The buyer-facing event is called Public page. See the Actor pricing page for the current price before you run it.

🔌 Integrations

Use the Apify API to start runs and read saved dataset rows. Use schedules for repeat searches, webhooks for the next step in a workflow, and dataset integrations for saved data.

❓ FAQ

How are duplicate pages handled?

The first eligible match for a public source item is saved. If another keyword, URL, or submitted value finds the same item later, that match is skipped and does not rewrite the saved row.

Can I mix keywords and direct Quora URLs?

Yes. Add both to targets. The page type and date range affect keyword discovery only. Direct question, profile, topic, space, post, or Quora search URLs are opened as given.

Can I choose the page type found by keyword search?

Yes. Choose question, profile, topic, space, post, or all. This choice does not change direct URLs.

Can I limit answers or filter them by upvotes?

Yes. Use answerDepth to choose top or all visible answers and minAnswerUpvotes to keep answers above a public upvote threshold. The question stays in the results even if no answer meets the threshold.

Does the date range filter direct Quora URLs?

No. It applies to keyword discovery when Quora shows a usable source date. It does not promise a Quora publish date, and direct URLs are opened as given.

What happens when Quora does not show a field or page?

A missing field is left out. A private, blocked, unsupported, or failed page does not make a saved row. Rows saved earlier in the run stay in the dataset.

How do I return all available results?

Leave maxResults empty. The Actor returns all available results until the source is exhausted.

Can I start a run with the Apify API?

Yes. Use the Apify API to start a run and read its saved dataset rows. Schedules, webhooks, and dataset integrations can support the next step.

Do I need a Quora account or API key?

No. The Actor uses public pages and does not ask for Quora cookies, login details, or an API key.

Does it collect private answers or answer comments?

No. It collects public page data only. It does not collect private, login-only, restricted, or Quora+ paywalled content, answer comment bodies, or commenter and upvoter identities.

📝 Changelog

2.0: Expanded public page search and structured results

• Search public Quora questions, profiles, topics, spaces, and posts by keyword or URL.
• Choose answer depth, answer filters, and result ordering for each run.
• Receive page-specific rows with visible answers and public metadata.

v1.0

• Updated the public dataset contract.
• Simplified the input form.
• Added public profile, topic, space, and post coverage.
• Introduced tiered saved-page pricing.

v0.1

• Initial release.

🆘 Support

For issues, questions, or feature requests, file a ticket and I'll fix or implement it in less than 24h 🫡

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Made with ❤️ by Maxime Dupré