Google AI Overviews increasingly cite Reddit threads as sources, especially for product recommendations, how-to questions, and community opinions. Tracking which Reddit threads get cited in AI Overviews reveals what content Google considers authoritative for specific queries. This tutorial shows how to query AI Overviews for a list of keywords, extract Reddit sources, and build a monitoring pipeline that tracks citation changes over time. You will identify which subreddits and post types consistently earn AI Overview citations.
Prerequisites
- Python 3.8+ installed
- requests library installed
- A Scavio API key from scavio.dev
- A list of keywords to monitor for Reddit citations
Walkthrough
Step 1: Query AI Overviews for Reddit sources
Search for keywords and extract Reddit-specific sources from AI Overview responses.
import os, requests
from datetime import date
API_KEY = os.environ["SCAVIO_API_KEY"]
def get_reddit_citations(keyword):
resp = requests.post("https://api.scavio.dev/api/v1/search",
headers={"x-api-key": API_KEY},
json={"platform": "google", "query": keyword})
aio = resp.json().get("ai_overview", {})
sources = aio.get("sources", []) if aio else []
reddit = [s for s in sources if "reddit.com" in s.get("link", "")]
return {"keyword": keyword, "reddit_sources": reddit, "total_sources": len(sources)}Step 2: Scan multiple keywords
Run the citation check across a list of target keywords.
KEYWORDS = [
"best vpn 2026",
"best crm for startups",
"how to learn python",
"best budget laptop",
]
citations = []
for kw in KEYWORDS:
result = get_reddit_citations(kw)
citations.append(result)
reddit_count = len(result["reddit_sources"])
print(f"{kw}: {reddit_count} Reddit citations / {result['total_sources']} total")Step 3: Extract subreddit patterns
Analyze which subreddits appear most frequently across AI Overview citations.
import re
from collections import Counter
def extract_subreddit(url):
match = re.search(r"reddit\.com/r/(\w+)", url)
return match.group(1) if match else "unknown"
all_subs = []
for c in citations:
for s in c["reddit_sources"]:
sub = extract_subreddit(s.get("link", ""))
all_subs.append(sub)
sub_counts = Counter(all_subs)
for sub, count in sub_counts.most_common(10):
print(f"r/{sub}: {count} citations")Step 4: Store daily snapshots
Save citation data daily to track changes over time.
import json
def save_snapshot(citations_data):
snapshot = {
"date": date.today().isoformat(),
"citations": citations_data,
}
filename = f"reddit_citations_{date.today().isoformat()}.json"
with open(filename, "w") as f:
json.dump(snapshot, f, indent=2)
print(f"Saved snapshot to {filename}")
save_snapshot(citations)Python Example
import os, requests
API_KEY = os.environ["SCAVIO_API_KEY"]
def reddit_citations(kw):
resp = requests.post("https://api.scavio.dev/api/v1/search",
headers={"x-api-key": API_KEY},
json={"platform": "google", "query": kw})
aio = resp.json().get("ai_overview", {})
sources = aio.get("sources", []) if aio else []
return [s for s in sources if "reddit.com" in s.get("link", "")]
for s in reddit_citations("best vpn 2026"):
print(s.get("link",""))JavaScript Example
const H = {"x-api-key": process.env.SCAVIO_API_KEY, "Content-Type": "application/json"};
async function redditCitations(kw) {
const r = await fetch("https://api.scavio.dev/api/v1/search", {
method: "POST", headers: H,
body: JSON.stringify({platform: "google", query: kw})
});
const aio = (await r.json()).ai_overview || {};
return (aio.sources || []).filter(s => (s.link||"").includes("reddit.com"));
}
redditCitations("best vpn 2026").then(rs => rs.forEach(s => console.log(s.link)));Expected Output
A monitoring pipeline that tracks which Reddit threads are cited in AI Overviews, identifies top-cited subreddits, and stores daily snapshots for trend analysis.