Socialprofiler
Launched this week
Find out what people are into based on their social media
577 followers
Socialprofiler helps you quickly and clearly understand who you're really dealing with online and offline. Whether you're dating someone new, hiring help at home, concerned about your kid's safety, or just curious—Socialprofiler gives instant insights.
SnoopReport
Hi Product Hunt, I’m Tony 👋
Five years ago we launched @SnoopReport here—while controversial, generally it seemed to be appreciated by the community.
Today we’re back with a new take on this classic problem. Socialprofiler instantly generates detailed interest profiles from public Facebook, Instagram, X, and TikTok profiles.
To generate a report, you just need a person’s first/last name & state, or their username.
Features:
Detailed insights into personal interests, beliefs, and values
Identification of potentially controversial or risky interests
Profile summaries covering politics, work background, locations, financial status, family, and even unusual aspects
So — I can already hear your concerns... I take them seriously!
What we’re offering really isn’t any different than Mark Zuckerberg’s Facebook newsfeed. The information we use is already public — we’re just collecting it and presenting it in an easy-to-use format.
For example, say I meet this guy Ryan Hoover at a hackathon and we want to explore founding something together. Wouldn't it be cool if I could see whether we have shared interests and might vibe?
Still not convinced? Let’s go deeper into this topic:
On behalf of the team, I’m super excited to invite the Product Hunt to try Socialprofiler, and I genuinely would love your feedback!
To give you a taste of what Socialprofiler can do, we’re giving everyone a free report for this week only when you sign up and use promo code PH. Try it on yourself (or someone you're curious about) right here:
https://socialprofiler.com/?promo=PH
Thanks
– Tony and the Socialprofiler Team
FYI: Currently available to U.S. customers only; more markets coming soon. We fully support user opt-outs and provide an easy form for this (subject to jurisdictional regulations).
@aenoskov How do you handle false positives from nickname matches?
Socialprofiler
@masump Thanks for a great question.
Socialprofiler is not an identity resolution service in the strict or legal sense. We don’t claim or guarantee that two profiles are the same person. Instead, we provide search optimization: helping users explore public social signals across platforms based on input parameters like name or state.
Our system is built to surface public content, respecting platform policies and individual privacy. Every result is probabilistic, not deterministic- and we don’t merge identities, we simply rank likely matches to aid discovery.
Think of it more like a smart search engine for public persona profiles.
At Socialprofiler, we use nickname mapping as just one of many signals in our discovery pipeline. A raw match like “Jon” = “Jonathan” is never enough to meaningfully boost a profile’s rank. We combine it with:
Contextual metadata (e.g., shared city, occupation, or education)
Posting patterns and time zones
Semantic content similarity
Graph-based co-occurrence
In short, we treat nickname overlap as a weak signal, and only act when it’s confirmed by multiple stronger signals.
This dramatically reduces false positives and optimize discovery search.
If our suggestion isn't accurate, you can refine the results by selecting the correct account from the search results or by entering the exact username in the username search field.
Definitely a bold one, but no denying the tech is powerful!! I feel like this is going to get a lot of attention...
The transparency around data use and the nod to ethics is appreciated, really feels like you’re tackling a complex space w/ eyes wide open.
Best of luck today!!
SnoopReport
@cranqnow Thanks so much! We spent nearly two years bringing this to life—lots of legal and ethical groundwork went into it as well. Appreciate the support!
Socialprofiler
Hey Product Hunt — I’m Artem, co-founder and the one behind the data science. 🧠 Drop me a comment if you want to talk about graph-based clustering of public social activity, graph theory, interest modeling etc.
Raycast
@korolevart hey Artem — tell us more about how graph theory applies to Socialprofiler... how different are your techniques from modern advertising platforms?
Socialprofiler
@chrismessina Hey Chris - awesome question. You've hit on the fundamental difference between our approach and traditional adtech.
Where adtech graphs are static and designed to put users in predefined boxes, ours is a living system designed to discover what's happening between the boxes.
We flipped the model. Instead of starting with labels, we find the communities and then interpret them. Here’s how:
A Graph That Infers Latent Interests: We go far beyond direct content. Our graph builds a multi-dimensional map of a user's interests by analyzing their social connections and followings. Crucially, this allows us to propagate interest patterns across the network. Even if a user is passive, we can reconstruct their likely preferences based on the interests of users in their immediate social circle.
Emergent, Multi-Modal Clusters: Our communities emerge organically from a mix of signals (content, inferred interests, behavior, and time), not just by grouping similar keywords. This means they constantly evolve, capturing the true pulse of a conversation as it happens.
LLMs for Interpretation, Not Just Classification: This is our secret sauce. We use LLMs to interpret these dynamic clusters and generate adaptive, narrative labels. If a community's focus drifts or a new sub-topic emerges, our system can spot it, understand it, and even split the cluster to reflect that change.
The end goal isn't conversion; it's discoverability, contextual depth, and cross-platform coherence. It’s about seeing the social web for what it truly is - a living network of interests.
Happy to jam on this further. Thanks again for the killer question!