https:\/\/graph.facebook.com\/v14.0\/{hashtag_id}\/recent_media<\/a>"
params = {"user_id": "YOUR_USER_ID", "fields": "id,caption,media_url", "access_token": token}
return pd.DataFrame(requests.get(url, params=params).json().get("data", []))<\/p>\ntoken = "YOUR_ACCESS_TOKEN"
df1 = fetch_hashtag_media(token, "17841562498179128") # hashtag1
df2 = fetch_hashtag_media(token, "17841562498179129") # hashtag2
common = pd.merge(df1, df2, on="id")
print(common)<\/p>\n
This snippet pulls two hashtag feeds and merges them on the id<\/code> column, instantly surfacing posts that carry both tags.<\/p>\n\nCombining endpoints, filters, and simple DataFrame operations lets you zero in on the exact posts you\u2019re tracking\u2014no guesswork needed.<\/p>\n<\/blockquote>\n
Visualizing Multi-Hashtag Trends<\/h3>\n
After you\u2019ve identified overlapping posts, it\u2019s time to chart the story. Aggregate daily counts of these intersections and feed them into your BI tool of choice\u2014think Metabase or Grafana.<\/p>\n
\u2022 Group query by date and hashtag set
\u2022 Highlight sudden spikes and annotate campaigns or events
\u2022 Automate weekly snapshot emails to stakeholders <\/p>\n
A well-annotated time-series chart not only serves you but also keeps everyone aligned on when and why certain tag combinations took off.<\/p>\n
Handling Pagination And Rate Limits<\/h3>\n
Instagram\u2019s API enforces both per-hour and per-user quotas. To navigate this: <\/p>\n
\n- Inspect
paging['next']<\/code> in each response and loop until exhausted <\/li>\n- Apply exponential backoff on HTTP 429<\/strong> responses <\/li>\n
- Track request timestamps to avoid more than 200 calls per hour<\/strong> <\/li>\n
- Cache responses locally to skip duplicated fetches across runs<\/li>\n<\/ol>\n
A controlled loop that respects these limits will run smoothly, even when you scale to dozens of hashtags.<\/p>\n
Integrating Alerts Into Slack Or Email<\/h3>\n
Once your script flags new multi-tag matches, push notifications to your team. Store your webhook URLs in environment variables, then send concise messages like this:<\/p>\n
import requests
def notify_slack(url, text):
requests.post(url, json={"text": text})<\/p>\n
Include the post link, timestamp, and a highlight from the caption or top comment. Group multiple alerts into digest mode if you\u2019re hitting high volumes\u2014no one needs hundreds of separate pings.<\/p>\n
Storing And Intersecting Results For Alerts<\/h3>\n
A relational database or time-series store makes historical comparisons a breeze. Structure your table with columns: post_id<\/code>, timestamp<\/code>, hashtags<\/code>. Then:<\/p>\n\u2022 Insert only new post_id<\/code> entries
\u2022 Use SQL joins to find IDs appearing across all target hashtag tables
\u2022 Trigger alerts only for genuine, fresh intersections <\/p>\nThis approach ensures you never re-notify on old content and keep alerts razor-focused.<\/p>\n
\nTrue multi-hashtag monitoring relies on the combination of API pulls and DB logic. That\u2019s how you stay on top of emerging conversations.<\/p>\n<\/blockquote>\n
Common Pitfalls And How To Avoid Them<\/h3>\n
\u2022 Missing paging<\/code> checks can cut your loop short. Always verify both "data"<\/code> and "paging"<\/code> before moving on.
\u2022 JSON parsing errors deserve their own try\/except<\/code> block\u2014malformed responses do happen.
\u2022 Over-caching hashtag IDs? Set clear TTLs to avoid stale mappings.
\u2022 Spammy or banned tags often return empty datasets. Run a quick manual check if one tag consistently fails.
\u2022 Test your full flow on a small tag set before scaling up.<\/p>\nImplement comprehensive logging\u2014record each API call, its parameters, and response codes. And, finally, set alerts on consecutive failures so you can troubleshoot before your reporting pipeline goes dark.<\/p>\n
Third Party Tools And Automation Tips<\/h2>\n
![\"Screenshot](\"https:\/\/cdn.outrank.so\/1e922346-1039-4a5b-a58a-5c7b1f430e4a\/736b240e-2ac1-4429-a52d-cae3e8af4750\/image.jpg\")
<\/figure>\n<\/p>\n![\"Search](\"https:\/\/cdn.outrank.so\/1e922346-1039-4a5b-a58a-5c7b1f430e4a\/9fc0f49b-dbd3-4329-a113-3767829b86a9\/image.jpg\")
<\/figure>\n<\/p>\n![\"Screenshot](\"https:\/\/cdn.outrank.so\/1e922346-1039-4a5b-a58a-5c7b1f430e4a\/b8487465-3ebb-415c-a5ab-15d2933e693e\/image.jpg\")
<\/figure>\n<\/p>\n