Instagram location API: mining posts by place

Locations are Instagram's underrated dimension: every geotagged post carries a place id, and every place id is a filter the platform curated itself. For local research — venues, neighborhoods, events — location mining beats keyword search on precision.

The two endpoints

GET /v1/ig/location/info/{pk}        # place card
GET /v1/ig/location/media/{pk}       # posts at the place, paginated

The location card returns name, address, coordinates and the media count — everything needed to verify you have the right place among same-named venues:

from getsocialapi import Client

ig = Client(api_key="gsa_live_...").instagram

loc = ig.location_info(pk)
print(loc["name"], loc.get("lat"), loc.get("lng"), loc.get("media_count"))

Walking the media

The location media route is native-page paginated: pass next_max_id back as max_id while it is returned. Items are the standard media shape — captions, counters, owners, timestamps.

posts, cursor = [], None
while True:
    page = ig.location_media(pk, max_id=cursor)
    posts += page["items"]
    cursor = page.get("next_max_id")
    if not cursor or len(posts) >= 500:
        break

One trap: the response also carries a next_page counter. It is a page number, not a cursor — using it as max_id returns Invalid Cursor. next_max_id or bust.

Where place ids come from

• Media items themselves: every geotagged post from user media or hashtag posts carries its location id in the payload.
• The venue's own Instagram profile often pins its place.

Harvest ids from any media stream you already collect, dedupe, then expand each into its own post set.

What location datasets answer

Question	Method
Footfall proxy	post volume per time bucket from taken_at
Venue popularity trend	media count + ER over rolling windows
Event detection	volume spikes vs baseline at a place
Local creator discovery	owners recurring across a place's posts
Competitive set	same-category venues within radius, via coordinates

Coordinates in the location card make radius queries trivial — harvest cards for all candidate venues, filter by haversine distance, then walk only the ones inside your fence.

Scale notes

A venue with 50k geotagged posts is ~2 500 pages at native size — checkpoint the cursor per location and resume across sessions (see the rate limits guide). For dense city-center research, sample by time window instead of full walks: the goal is usually the distribution, not the census.

Place ids in, posts out — getsocialapi.com, first 100 calls free.

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