4) We download all transactions for each wallet and build a graph of counter-agents. There are quite a lot of counter-agents, so we filter only those wallets that have appeared in the transaction history more than n times. For the resulting counterparty wallets, we will repeat steps 2 and 3. Perhaps among them there are wallets with a small capitalization, but a large predictive potential.
Below you can see the number of wallet nodes (white) and counterparties (black) with different parameters for the threshold of connections to be added to the graph. The larger the parameter, the fewer counterparties remain: