🎟️ Facebook Events Scraper: Multi-City Search & Ticket Price

Facebook Events Scraper — Events, Ticket Prices and City Data

Facebook Events Scraper turns keyword searches into a structured feed of public Facebook events — event name, URL, date/time sentence, address, coordinates, organizer, going/interested counts, and parsed ticket pricing (ticketCurrency, ticketPriceMin, ticketPriceMax, isFreeEvent). Search a list of cities against your keywords in one run instead of many manual searches. Event marketers, ticketing analysts, local SEO agencies, and market researchers use it to compare event pricing and coverage city by city. Every row lands in a ready-to-export Apify dataset.

🎟️ What is Facebook Events Scraper?

Facebook Events Scraper is an Apify Actor that discovers public Facebook events by keyword and returns a structured JSON/CSV row per event — no Facebook login or developer account required. It finds event pages through Google's public search index (site:facebook.com/events <query>) rather than Facebook's own search, then fetches each event's public page for the full details. On top of the standard fields it adds two built-in upgrades: structured ticket pricing parsed from Facebook's raw price text, and multi-city bulk discovery that cross-produces your keyword list against a list of cities in a single run.

• 🔎 Discovery by free-text keyword — one query per line in searchQueries, no category taxonomy required
• 🌆 Multi-city cross-product — add cities and every keyword is searched once per city automatically
• 🎟️ Ticket price parsing — raw price text like "$10 - $50" is split into currency, min, max, and a free/paid flag
• 📍 Location data — venue name, street address, city, country code, and latitude/longitude when Facebook exposes them
• 🧑‍💼 Organizer extraction — host name, profile/Page URL, and a verification flag per organizer
• 💾 Standard Apify export formats — JSON, CSV, Excel, XML, HTML, or the Dataset API

📊 What data can I extract with Facebook Events Scraper?

Every field below is written by the row-building code in src/main.py (build_event_stub plus the fields enrich_event_with_details fills in) — not just the default dataset view.

Field	Example value	Use case
url	"https://www.facebook.com/events/1202620635007207/"	Canonical event link
id	"1202620635007207"	Stable Facebook event ID
name	"Downtown Jazz Night"	Event title
searchKeyword	"jazz night"	Which input query produced this row
queryCity	"Chicago"	Which city (multi-city mode) produced this row, or null
dateTimeSentence	"FRIDAY, AUGUST 21 2026"	Upper-cased human date/time sentence
startTime	"Friday, August 21 2026"	Raw human date sentence (not a fixed-format timestamp)
utcStartDate	null	Reserved field — see limitation below
eventFrequency	"SINGLE"	Recurrence type; "SINGLE" unless Facebook's own payload states otherwise
imageUrl	"https://scontent.xx.fbcdn.net/…"	Event cover image
imageCaption	null	Reserved field, currently always null
duration	"3 hr"	Display duration text, when Facebook exposes it
description	"Party event in Chicago…"	Full event description text
address	"123 Main St, Chicago, US"	Best-effort composed address string
location	{ "name": …, "city": …, "countryCode": …, "latitude": …, "longitude": … }	Structured venue object (10 keys — see below)
usersGoing	76	Parsed "going" count
usersInterested	240	Parsed "interested" count
usersResponded	316	usersGoing + usersInterested (derived, not a separate Facebook field)
ticketsInfo	{ "price": "$10 - $25", "buyUrl": null, "title": "Tickets · $10 - $25", "subtitle": …, "ticketProvider": … }	Raw ticketing-widget payload, or null if the event has no ticketing widget
ticketCurrency	"USD"	Parsed from the price text's currency symbol
ticketPriceMin	10	Parsed lowest price
ticketPriceMax	25	Parsed highest price
isFreeEvent	false	true/false when a price is parsed, null when there is no ticketing data at all
ticketBuyUrl	null	Populated only when Facebook's own payload exposes a real buy URL
organizedBy	"Blue Room Chicago"	Primary organizer/host name
organizators	[{ "name": …, "id": …, "url": …, "isVerified": false }]	Full organizer list
eventType	"PUBLIC"	Constant value — see limitation below
privacyInfo	"Public · Hosted by Blue Room Chicago"	Composed privacy sentence
isPast	false	Constant value — see limitation below
isOnline	false	Constant value — see limitation below
isCanceled	false	Constant value — see limitation below
hasChildEvents	false	true when recurring child occurrences were found
childEvents	[]	[{ "id", "url", "name", "dateTimeSentence" }] when recurring occurrences exist
discoveryCategories	[]	[{ "url", "label" }] Facebook discovery-category tags, when present
externalLinks	[]	Unique external URLs found in the description
externalLinksSource	null	Reserved field, currently always null
scrapedAt	"2026-08-04T09:00:00.000Z"	ISO scrape timestamp
inputUrl	"/events/search/?q=jazz%20night%20Chicago"	Relative Facebook search path the query would have used
discoverySource	"google_serp"	Constant — how this actor discovers event URLs (see below)

🎫 Ticket pricing data

ticketsInfo, ticketCurrency, ticketPriceMin, ticketPriceMax, and isFreeEvent are populated only when the event's own detail page carries a ticketing widget. The raw price text (e.g. "$10 - $50", "Free", "£5") is parsed with a currency-symbol lookup and a number extractor — never guessed. Events with no ticketing widget at all get ticketsInfo: null and isFreeEvent: null, which is deliberately different from isFreeEvent: true: "no price data" and "confirmed free" are not conflated. Use freeOnly: true to keep only confirmed-free events, or filter on ticketPriceMax client-side to build a price-tier comparison across cities.

🌆 Location and targeting data

location.city, location.countryCode, location.latitude/longitude, queryCity, and searchKeyword are the fields you filter and group on. queryCity and searchKeyword are tagged on every row so a multi-city run can be split back out per city or per keyword after the fact, without re-running anything.

🤔 Why not build this yourself?

Facebook's own anonymous events-search GraphQL endpoint is login-gated platform-wide — this actor's own source confirms it was still gated as of 2026-08-01 across independent live probes. A DIY scraper would need to either authenticate as a real Facebook user (against Facebook's terms and a ban risk) or find another discovery path entirely. This actor instead discovers event URLs through Google's public search index and reads each event's own public detail page for the real data — no login, no cookies, no account.

Even with a working discovery path, a DIY build still has to solve: rotating residential proxies (Facebook blocks datacenter IPs quickly), retry/backoff on 403/429/blocked/rate limit responses, parsing ticket pricing out of free-text widget payloads instead of a stable field, and re-deriving address/organizer/coordinate data from nested JSON blobs embedded in the page HTML rather than a documented API response shape. This actor already does all of that, with automatic proxy rotation and exponential-backoff retries (up to 3 attempts per request) built in.

Build it yourself if you need a fully custom discovery mechanism (e.g. your own Facebook session) or want to avoid any dependency on Google's index. Use this actor if you want a working keyword-to-structured-event pipeline today, with ticket pricing and multi-city search already solved.

🧭 How to use data extracted from Facebook Events

📅 Event marketers and promoters

Feed searchQueries with your event category and cities with your target markets, then use ticketPriceMin/ticketPriceMax and usersGoing/usersInterested to benchmark your own pricing and expected turnout against comparable public events in the same city before setting your own ticket price.

🏢 Agencies and ticketing consultancies

Run the same searchQueries across a client's target cities on a recurring schedule, and diff usersGoing/usersInterested/ticketPriceMin/ticketPriceMax between runs to show clients how demand and pricing for their event category are trending in each market — a repeatable audit rather than a one-off pull.

📈 Market research and intelligence

Cross a category keyword (e.g. "comedy show") against a city list to build a price-distribution and turnout table across markets in a single run, using queryCity, ticketPriceMin, ticketPriceMax, and usersGoing as the grouping and comparison fields — useful for city-selection and pricing-benchmark research.

🤖 AI agents and automated pipelines

Because output is typed JSON keyed by stable field names, an agent can call this actor as a tool to answer "what's happening in {city} this week that matches {keyword}" and reason directly over dateTimeSentence, address, and ticketPriceMin/ticketPriceMax without a separate parsing step.

🔼 Input sample

Read directly from .actor/actor.json. searchQueries is the only required field; everything else has a default and is fully optional.

Parameter	Required	Type	Description	Example value
searchQueries	Yes	array	Keywords to search for on Facebook Events, one per line. Every query is processed in order.	["jazz night", "tech meetup"]
cities	No	array	Optional list of cities to cross with every search query. Leave empty to search each query as-is. Default [].	["Chicago", "Austin", "Denver"]
maxEvents	No	integer	Stop after this many events per search combination (each query, or each query × city pair). Allowed 1–1000, default 10.	25
freeOnly	No	boolean	When true, only events whose parsed ticket price resolves to free (isFreeEvent = true) are returned. Default false.	false
proxyConfiguration	No	object	Apify Proxy configuration. See the limitation below — this input is not read for the actual event-page fetch.	{ "useApifyProxy": false }

{
  "searchQueries": ["jazz night"],
  "cities": ["Chicago", "Austin", "Denver"],
  "maxEvents": 25,
  "freeOnly": false,
  "proxyConfiguration": { "useApifyProxy": false }
}

⚠️ Common pitfall: proxyConfiguration is present in the input schema for consistency with sibling actors, but the source (setup_proxy_with_fallback in src/main.py) always fetches Facebook event pages through the RESIDENTIAL Apify Proxy group regardless of what you set here — a documented, deliberate choice because Facebook is unreliable enough on datacenter or no-proxy IPs to cause silent zero-row runs. Don't expect a custom proxy group/country to change how event pages are fetched.

🔽 Output sample

Every row is pushed to the dataset as typed, normalized JSON with a consistent schema — export as JSON, CSV, Excel, XML, or HTML from the Apify Console, or read it via the Dataset API.

{
  "url": "https://www.facebook.com/events/1202620635007207/",
  "id": "1202620635007207",
  "name": "Downtown Jazz Night",
  "searchKeyword": "jazz night",
  "queryCity": "Chicago",
  "dateTimeSentence": "FRIDAY, AUGUST 21 2026",
  "utcStartDate": null,
  "startTime": "Friday, August 21 2026",
  "eventFrequency": "SINGLE",
  "imageUrl": "https://scontent.xx.fbcdn.net/v/example.jpg",
  "duration": null,
  "description": "Party event in Chicago, IL by Blue Room Chicago on Friday, August 21 2026 with 240 people interested and 76 people going.",
  "address": "The Blue Room, Chicago, US",
  "location": {
    "url": null,
    "id": null,
    "name": "The Blue Room, Chicago",
    "contextualName": "The Blue Room, Chicago",
    "placeType": "PLACE",
    "latitude": 41.8781,
    "longitude": -87.6298,
    "countryCode": "US",
    "streetAddress": null,
    "city": "Chicago"
  },
  "usersGoing": 76,
  "usersInterested": 240,
  "usersResponded": 316,
  "ticketsInfo": { "buyUrl": null, "price": "$10 - $25", "title": "Tickets · $10 - $25", "subtitle": "eventbrite.com", "ticketProvider": "eventbrite.com" },
  "ticketCurrency": "USD",
  "ticketPriceMin": 10,
  "ticketPriceMax": 25,
  "isFreeEvent": false,
  "ticketBuyUrl": null,
  "organizedBy": "Blue Room Chicago",
  "organizators": [{ "name": "Blue Room Chicago", "id": null, "url": null, "isVerified": false }],
  "eventType": "PUBLIC",
  "privacyInfo": "Public · Hosted by Blue Room Chicago",
  "isPast": false,
  "isOnline": false,
  "isCanceled": false,
  "hasChildEvents": false,
  "childEvents": [],
  "discoveryCategories": [],
  "externalLinks": [],
  "scrapedAt": "2026-08-04T09:00:00.000Z"
}

A per-city/per-query result-count summary ({ "searchKeyword", "city", "eventsCollected" } rows) is also written to the run's key-value store under CITY_QUERY_SUMMARY whenever cities is used.

🎯 How do you filter and target specific events?

This actor's targeting surface is intentionally small — four real controls, no category taxonomy or radius search:

1. Free-text query, not category. searchQueries is a plain keyword list — there is no fixed category enum. Specific, concrete phrases ("jazz night", "5k charity run") return more relevant results than broad ones ("music").
2. City scoping via text, not coordinates. cities appends each city name to the query text ("jazz night" + "Chicago" → "jazz night Chicago") rather than a lat/long radius — there is no bounding-box or distance-radius parameter.
3. Price threshold, not a rating filter. freeOnly is the one quality/segment filter this actor exposes — it keeps only events with a confirmed-free parsed price, leaving unknown-price events in either mode.
4. Volume control. maxEvents (1–1000, default 10) caps results per keyword/city combination, but see the pagination limit below — setting it above roughly 60–70 will not return more results for a single combination.

{ "searchQueries": ["food truck festival"], "maxEvents": 50 }

{ "searchQueries": ["salsa night"], "cities": ["Miami", "Los Angeles"], "freeOnly": true }

{ "searchQueries": ["startup networking", "tech meetup"], "cities": ["Austin"], "maxEvents": 15 }

⚠️ Real limit: discovery goes through Google's public search results (discover_event_urls_via_google_serp in src/main.py), which pages up to start=60 (roughly 7 result pages) and stops early after 2 consecutive pages with no new event URLs. In practice this caps a single keyword/city combination at roughly 60–70 unique discoverable events even though maxEvents accepts values up to 1000 — a higher maxEvents only helps once a query naturally surfaces more results.

▶️ Want to try other Facebook and directory scrapers?

Scraper	What it extracts
Facebook Group Posts and Details Scraper	Facebook group posts, member profiles, and public contact leads
LinkedIn Search Jobs Scraper (Advanced Search Filters)	Job listings with salary, seniority, and advanced filter fields
Tripadvisor Review Scraper (Photo and Visual Content Filters)	Business listings, reviews, ratings, and photo/visual content
TikTok Shop Data Scraper (Reviews and Sentiment Analysis)	Product listings, reviews, and sentiment-scored feedback
Pinterest Ads Scraper (Performance Analytics)	Ad listings with performance/analytics fields

💻 How to extract Facebook event data programmatically

This actor runs as a standard Apify Actor: one API call, your Apify API token as the auth header, structured JSON back from the Dataset API.

Python example

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_API_TOKEN>")

run = client.actor("SimpleAPI/facebook-events-scraper-multi-city-search-and-ticket-price").call(
    run_input={
        "searchQueries": ["jazz night"],
        "cities": ["Chicago", "Austin"],
        "maxEvents": 25,
        "freeOnly": False,
    }
)

for event in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(event["name"], event["queryCity"], event["ticketPriceMin"], event["ticketPriceMax"])

📊 Export to spreadsheets or CRM

Export the dataset directly as CSV or Excel from the Apify Console (or the Dataset API's format=csv/format=xlsx parameter) and map columns straight from the JSON keys — name → event name, ticketPriceMin/ticketPriceMax → price range columns, address and location.city → location columns, organizedBy → contact/organizer column.

⚖️ Is it legal to scrape Facebook Events data?

Scraping publicly accessible Facebook event pages is generally permitted; these listings exist specifically to be discovered and shared, and this actor only reads pages Facebook already serves to logged-out visitors. Most of the data — event name, date, description, ticket price, attendance counts — is public promotional content, not personal data, so it falls under Facebook's Terms of Service rather than data-protection law. The organizedBy/organizators fields can identify an individual host rather than a Page or business, and in that case GDPR/CCPA-style rules on lawful basis for storage and use of personal data may apply to that subset of the data. Consult legal counsel for commercial applications involving bulk storage of personal data.

❓ FAQ

Does this actor mark events as past or canceled?

No — isPast and isCanceled are always false in the current output; this actor does not detect event recency or cancellation status. Cross-check dateTimeSentence/startTime against today's date yourself if you need to filter out events that have already happened.

Can I get ticket price data along with the main event records?

Yes, in the same row — ticketCurrency, ticketPriceMin, ticketPriceMax, and isFreeEvent are parsed automatically whenever an event's detail page carries a ticketing widget. Events with no ticketing widget return null for all four fields rather than a fabricated 0.

How accurate is the date and price data?

The actor returns data exactly as it appears on the public event page at request time. dateTimeSentence/startTime are extracted from a natural-language sentence (not a machine-parsed timestamp — utcStartDate is currently always null), so treat them as display text and re-parse if you need a strict date type. Ticket prices reflect whatever text Facebook's ticketing widget shows; recommend spot-checking against the ticketBuyUrl before using prices for anything transactional.

How many events can I get per run?

maxEvents accepts 1–1000 per keyword/city combination, but Google-SERP-based discovery realistically exhausts after roughly 60–70 unique events per combination (see the pagination limit above) — set maxEvents near that ceiling for a single keyword rather than expecting 1000 results from one query.

How does the multi-city search work?

Every keyword in searchQueries is combined with every city in cities (2 keywords × 3 cities = 6 scoped searches), each capped independently by maxEvents. Leave cities empty and it behaves as a plain single-keyword search with no city scoping — fully backward compatible.

Does Facebook Events Scraper work with Claude, ChatGPT, and AI agent frameworks?

There is no dedicated MCP server for this actor. It is callable as a standard Apify Actor via the REST API or apify-client/apify-client-js from any agent framework that can make an authenticated HTTP call and read back JSON.

How does Facebook Events Scraper compare to other Facebook scrapers?

This actor's two built-in differentiators — structured ticket-price parsing (currency/min/max/free-flag) and multi-city keyword cross-product in a single run — come from its own input schema and source code, not a competitor comparison. Check any other Facebook events actor's own live Apify Store listing for whether it documents equivalent ticket-pricing or multi-city fields before assuming it does.

Can I use this without a Facebook API key or developer account?

Yes. No Facebook login, cookie, or developer account is required — only an Apify account to run the actor. Discovery goes through Google's public search index and every page fetched is a public, logged-out Facebook page.

✅ Conclusion

Facebook Events Scraper turns a keyword list into structured, exportable Facebook event data — with ticket pricing parsed into currency/min/max/free fields and multi-city search built in as a single run instead of many. It's built for event marketers, ticketing agencies, and market researchers who need city-by-city event and pricing coverage without a Facebook login. Run it from the Apify Console or call it via the API to get your first structured dataset in minutes.