Instagram hashtag mining: search, info and posts through an API

Hashtags are Instagram's own taxonomy. Mined properly, a seed word expands into its whole semantic neighborhood — every competitor tag, sized by volume, with the posts to back it. Three endpoints do it.

Step 1: search the neighborhood

GET /v1/ig/hashtag/search/{query}

The hashtag search returns every tag matching the query with its media count — #gymgirl, #gymgirlfit, #gymgirls… This is the expansion step: from one seed to the full variant list, volume-ranked:

from getsocialapi import Client

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

tags = ig.hashtag_search("gymgirl")["results"]
for t in sorted(tags, key=lambda x: -x.get("media_count", 0)):
    print(t["name"], t["media_count"])

A leading # is accepted and trimmed — #gym girl resolves the same as gymgirl.

Step 2: size each tag

GET /v1/ig/hashtag/info/{tag}

Hashtag info resolves a tag to its id and authoritative media count. In search results the counts can be cached; before committing crawl budget, re-check the finalists.

The volume tiers that matter:

Media count	Tier	Strategy
10M+	mega	visibility lottery; poor targeting
100k–10M	competitive	where ranking is realistic
1k–100k	niche	high relevance, low reach — mix in

Step 3: walk the posts

GET /v1/v2/hashtag/posts/{tag}?max_id=<cursor>

Hashtag posts return the native page (~15–18 posts) with next_max_id for pagination. Items carry caption, like/comment counts, owner and timestamps — everything needed for engagement-rate scoring per tag:

posts, cursor = [], None
while True:
    page = ig.hashtag_posts("#gymgirl", max_id=cursor)
    posts += page["posts"]
    cursor = page.get("next_max_id")
    if not cursor or len(posts) >= 200:
        break

avg_er = sum(p["like_count"] for p in posts) / len(posts)

What the dataset answers

• Tag selection — relevance × competitiveness × observed engagement, per variant.
• Posting patterns — taken_at histograms: when a tag's audience actually posts (proxy for when they browse).
• Creator discovery — owners recurring across a tag's top posts are its real community anchors; pull their profiles next.

Scale honestly

A 50-tag neighborhood at 200 posts each is ~700 requests. Checkpoint next_max_id per tag — cursors are stable strings, so the crawl can resume across days within plan limits.

Search, size, walk — three calls, one dataset, on getsocialapi.com. First 100 free.

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