Most blockchain analytics systems use a graph as a tool for visualizing relationships.

The reader is probably wondering why an ordinary user needs such a tool as a graph, if he is familiar with the basics of cryptocurrencies and knows that public blockchains are publicly available and the movement of his funds can be viewed in such observers as blockchain.com, etherscan.io and other similar programs.

Yes, it is true that the functionality of the observers allows you to understand the movement of funds, but this is true if it is a direct chain of links that goes from one address to another. If funds are distributed to several addresses in the course of movement and there is a need to track each branch, and if such chains and branches appear in the process of research constantly and in addition have a length of 50 or more knees – in this case you cannot do without visualization of these links.

Transaction graph analysis allows to obtain information about the connection of certain addresses with each other and track the movement of funds. At the same time, it provides “new knowledge” (additional information) to a private researcher, who, unlike law enforcement officers, has no opportunity to send a request to an exchange or exchange service to disclose information about the affiliation of accounts.

What makes a link graph convenient for an analyst:

• Visual representation of long and complicated chains of links that are difficult to keep in your head;
• Quickly establishing the input and output paths to/from a researched address, as well as its known connections, using address markup;
• Determining whether participants in the events under investigation used “dirty funds”, giving us the potential possibility that these funds may have been blocked on centralized exchanges;
• Clearly identifying heuristics between addresses and determining from them the paths of funds and whether groups of addresses belong to the same owner;
• Search for recurring patterns of funds flow in a graph in one or more studies to disseminate patterns and data about possible addresses belonging to a single beneficiary.

All these advantages will allow an analyst to quickly and efficiently solve the task of analyzing addresses in blockchain networks, conduct a cryptocurrency investigation and come to conclusions for further step