Facebook Posts Search - This Apify Actor searches for posts on Facebook based on keywords or hashtags. The results include post url, post content, publication date, author information, and engagement metrics. - It is a perfect tool for monitoring Facebook for brand mentions over time Stay ahead of potential reputation risks, respond to significant events, and engage with highly active public discussions 🚀 --------------- ## Features - 🔍 Search by keywords, hashtags - 📅 Filter by location - 📊 Extract likes, comments, reactions etc. - 🖼️ Retrieve images and links from posts ## Input Parameters | Parameter | Type | Required | Description | |----------------|----------|----------|--------------------------------------------------------------------------------------------------------------| | query | string | ✅ | Keyword to search posts for. | | resultsCount | number | ❌ | Maximum number of posts to extract (e.g. 30). If not set, only a few of the first posts will be returned. | | location | string | ❌ | Search posts with pinned location. E.g. London, Mexico, Disneyland | | searchType | string | ❌ | Search type: most popular - top (default) or latest. Defaults to platform’s default if not specified. | ## Example Input json { "query": "Orange", "resultsCount": 50, "searchType": "latest" } ## Output Data The actor returns an array of JSON objects with extracted post data. ### Example Output json [ { "url": "https://www.facebook.com/jeff.moerke.1/posts/pfbid02gAfuzjGqHuAk9APdU6mDwveqeNg7cXf3YrEyFohYjwu8F2zgxgzSayXZ4bXHEZHHl", "timestamp": 1743735597000, "postText": "🍾Dom Daily🍾\nLV Collection on Point🕺🏻💃\n40 Bottles in 40 days\n 2009 Dom Pèrignon at @themonarchsteakhouse.aspen 🤑 needed something to wash down the caviar. \n\nSquad has pieces on pieces \n#jeffmoerke #hospatality #dompérignon #louisevuitton #aspen @louisvuitton @domperignonofficial @domperignoncollectors", "reactionsCount": 251, "reactions": { "like": 218, "love": 30, "support": 3, "haha": 4, "wow": 5, "sorry": 6, "anger": 1 }, "commentsCount": 1, "postId": "1891857264894411", "author": { "id": "100022104669475", "name": "Jeff Moerke", "profilePicture": "https://scontent.fpoz3-1.fna.fbcdn.net/v/t39.30808-1/328653743_672376154638502_2292484167379744319_n.jpg?stp=cp0_dst-jpg_s40x40_tt6&_nc_cat=105&ccb=1-7&_nc_sid=e99d92&_nc_ohc=wzuppsF7tW4Q7kNvwG8Jokm&_nc_oc=AdmCjeJrDYFOkExMlTro1Go_4aIZPGVCdSU0isBvxAsSEUTMOOyND1H0-a5J1ilYdCg&_nc_zt=24&_nc_ht=scontent.fpoz3-1.fna&_nc_gid=3HnVNoc9LAaE2-rhHqoH3Q&oh=00_AYEWhweOAbsVEla31p_H1Lrg5kMPajznKLyvr7UEUAZjwA&oe=67F57505", "profileUrl": "https://www.facebook.com/jeff.moerke.1" }, "attachments": [ { "type": "video", "url": "https://www.facebook.com/jeff.moerke.1/videos/521227401036554/", "id": "521227401036554" }, { "type": "photo", "url": "https://www.facebook.com/photo.php?fbid=1891857228227748&set=a.197904564289698&type=3", "id": "1891857228227748", "accessibilityCaption": "May be an image of text that says \"AplPay LOUIS VUITTONNEW YORK NY Mar 30, 2025 $3,628.76 AplPay LOUIS VUITTONNEW YORK NY Feb 24, 2025 $541.24 LOUIS VUITTON USA, INEW YORK NY Feb 2, 2025 $1,825.31 LOUIS VUITTON USA, INEW YORK NY Feb 2, 2025 $12,398.11 LOUIS VUITTON USA, INEW YORK NY Feb 1, 2025 $964.54 LOUIS VUITTON USA, INEW YORK NY Coh1 2025 $5,711.36\"" } ] } ] ##### Let us know if you need any other output fields. 🤙 ## Usage 1. Create an Apify account and navigate to the actor. 2. Configure input parameters in the Apify UI or via API. 3. Run the actor and monitor execution logs. 4. Download extracted posts as JSON, CSV, or Excel. ## Limitations & Notes - Scraping Facebook data must comply with their Terms of Service. - Avoid excessive scraping to prevent IP bans. - Rate-limited – Free users can make only a few requests per day. Contact us if you need higher or custom limits! ## Works Best With To maximize the effectiveness of this scraper, use it in combination with Facebook Comments Scraper. By first extracting Facebook posts with this scraper, you can then pass the collected post URLs into the Facebook Comments Scraper, allowing you to retrieve comments associated with those posts. ### Best Use Case Scenario - 🔎 Run Facebook Posts Search actor → Collect a list of posts based on keywords. - 📥 Feed post URLs into Facebook Comments Scraper → Extract comments from the collected posts for deeper analysis. - 📊 Get full post insights → Combine post metadata and comments for a complete dataset. This workflow is ideal for social media monitoring, sentiment analysis, and engagement tracking. 🚀 ## Other Recommended Scrapers If you're working with multiple platforms or want additional data sources, check out these scrapers: - 🐦 X (Twitter) Posts Search — Find posts/tweets based on keywords, hashtags, and more - 🐦 X (Twitter) Post Replies Scraper — Scrap replies of multiple X (Twitter) posts - 🐦 X (Twitter) Profile Posts Scraper — Scrap posts of specific X (Twitter) profile - 📘 Facebook Posts Search — Discover Facebook posts for a given topic or page - 📘 Facebook Comments Scraper — Extract comments from public Facebook posts - 📘 Facebook Reactions Scraper — Scrap reactions from Facebook posts (like, sad, haha, angry etc.) - 📘 Facebook Posts Scraper — Scrap posts from Facebook pages, groups etc. - 👟 Zalando Price Alert — Track Zalando products and receive alerts when prices drop - 🎬 YouTube Search Scraper — Extract videos from search queries - 🎬 YouTube Comments Scraper — Extract comments from posted videos - 🍔 Big Mac Price Scraper — Get the most current Big Mac prices around the world ## Support & Contact ✉️ If you encounter issues or need help, feel free to open an issue or contact us at scraper1one@gmail.com