We released a major update to our algorithm. Learn more here

About Us

We are a group of crypto minded researchers, engineers, designers and just fans of this space. We set out to build an algorithm which would provide a relevant context score to a users social channel. With this we first started with Twitter to get our baseline scoring mechanisms in place. We call algorithm Peoplerank. It works similar to how Google's Pagerank works, but instead of applying the relevance score to a webpage our algorithm applies that score to the conversations or messages being sent over a channel. Originally, Hive.One was called CryptoInfluencers.io which we decided to change the name, for more information you can read why here.

The Crypto Ecosystem

Crypto is a large, global, unstructured network. We believe that it’s the first of its kind.

On one hand, it’s similar to a startup ecosystem. But startup ecosystems came out of specific cities and were largely dependent on personal iterations. They were local first, global second networks.

On the other hand, it’s similar to the academic network. But scientists don’t raise or invest money. They rely on the support of institutions they work for. They form a global first, local second network, but financial capital does not flow freely through this network like it does in crypto.

We estimate that there are already over 1 million people in the crypto community. And this number is growing.

No human can keep up with this number of people.


We believe that a key to map such a network is to quantify how attention flows through it. Influence of individual members of this group is predicated on how much attention they receive from the rest of the group

That’s the reason we say we use mathematics for the mapping. In particular, we conduct lots of cluster analysis and bayesian inference.

The goal is to describe this network mathematically, so that one can get a reliable information about a given person’s or group’s role without even knowing the name.

It is possible to do that with other networks. For instance a corporation or an army. Knowing that somebody is a “director of distribution” or a “colonel” tells us a lot about the role of a person in a given group, without revealing their name or any other information.

Building Useful Things

Once this network is described mathematically, lots of new, useful products can be built using this information.

To start with, we are introducing three products:

- Lists of influential people in given communities. These take the forms of the tables you can browse on the homepage.
- Profiles of individual people. These display more detailed information and the list of clusters a given person belongs to. You can open profiles by clicking on a given name in the table.
- Personal Analytics tool. This tool is designed to provide you more information about yourself. Not only we want to show your scores in specific clusters, but also map your network, so that it’s easier for you to keep track of who is following and interacting with you. You can try it out now by going here.

More importantly, we have an open API. You can apply for access here.