Cross-Platform Social Search (24 Platforms)

Cross-platform social search is the ability to ask one question and search many social platforms at once — then get a single answer that dedupes the overlap and cites every claim to a real post. Superlurk covers 24 platforms across two retrieval lanes: eight native platforms that return real API metrics, and sixteen web-search-backed platforms that widen coverage with partial metrics. Five are searched by default. This guide explains how those lanes work, why the overlap gets merged into one cited answer, and when to go wide versus narrow.

What is cross-platform social search?

Every platform has its own search box, its own ranking, and its own quirks. Researching a topic properly used to mean opening TikTok, then Instagram, then Reddit, then YouTube, running the same query four times, and stitching the results together in your head. Cross-platform search collapses that into a single question.

You ask once — "what are people saying about the new Rabbit R1?" — and Superlurk retrieves the most relevant posts from every selected platform, reads them together, and writes back one answer where each claim links to its source. It's the foundation of social media search: the difference between checking one room and listening to the whole building.

Which 24 platforms does it cover?

Coverage breaks into two lanes by how each platform exposes its data.

• Native (real API metrics): TikTok, Instagram, YouTube, X, Reddit, LinkedIn, Threads, Lemon8.
• Web-search-backed (partial metrics): Facebook, Pinterest, Quora, Bluesky, Twitch, Hacker News, Product Hunt, GitHub, Medium, Substack, Snapchat, Tumblr, Telegram, Trustpilot, G2, Polymarket.
• Native comments mined directly: TikTok, Instagram, YouTube and X.
• Selected by default: TikTok, Instagram, YouTube, X and Reddit.

What's the difference between native and web-backed platforms?

The two lanes exist because platforms differ wildly in what they let you measure. Native platforms return trustworthy engagement counts you can rank on; web-backed platforms widen the net so niche communities aren't invisible, at the cost of full metrics.

Why only five platforms by default?

Searching all 24 platforms on every question would be slower and noisier than most questions need. So Superlurk defaults to five — TikTok, Instagram, YouTube, X and Reddit — the platforms that cover the widest mix of creators, video, discourse and real-time conversation.

You expand or narrow that set per query. Researching B2B? Add LinkedIn. Chasing a developer tool? Bring in Hacker News, GitHub and Product Hunt. Studying reviews? Pull in Trustpilot and G2. The default is a sensible starting point, not a cage.

How does it dedupe into one cited answer?

The same story often shows up everywhere — a product launch gets a TikTok, an Instagram Reel, a Reddit thread and a dozen reposts on X. Cross-platform search has to recognize that overlap and merge it, so you read one clear answer instead of the same point five times.

1. 1

   Retrieve in parallel

   Each selected platform is searched at once — native lanes through the API, web-backed lanes through search providers.

2. 2

   Normalize and dedupe

   Near-duplicate posts and reposts are collapsed so a single story counts once, not five times.

3. 3

   Rank by evidence

   What's left is ranked by relevance and real engagement, with native metrics weighted as the most trustworthy.

4. 4

   Answer with citations

   The result is one written answer where every claim links to a specific post, with a Sources tab listing each platform, author and metric.

How do platform-specific searches fit in?

Cross-platform is the default, but sometimes you want a deep, single-platform read. The platform guides go deeper on what each lane does well:

• [TikTok search and analytics](/blog/tiktok-search-analytics) — sounds, Shop signals and native comments on short video.
• [Instagram creator search](/blog/instagram-creator-search) — creators, hashtags and native comments for lifestyle and product.
• [X (Twitter) listening](/blog/x-twitter-listening) — the real-time conversation, share of voice and trend velocity.

Each of those is the same engine pointed at one platform; cross-platform search is what you reach for when you need the whole picture at once.

When should you go wide versus narrow?

Use breadth to validate, depth to understand. If you want to know whether a trend is real everywhere or confined to one app, go wide. If you want to study how a specific platform behaves — its creators, formats and metrics — go narrow.

• Go wide to measure share of voice across the whole conversation or confirm a signal isn't platform-specific.
• Go narrow to find creators on one platform with the Creator Finder or to study a single audience in depth.
• Mix depths — run Quick to scope, then Deep or Max on the version that has to hold up. Compare on pricing.