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Wallet Interaction Labels
A tool for Web3 experts, only for DappRadar PRO members
When developers list a dapp on DappRadar, they can select the product category and some tags that fit their product. However, based on the types of users that interact with a dapp, one can also learn a lot about the platform's economy and community. That's where Wallet Interaction Labels come into play.
Wallet Interaction Labels reached their second iteration after receiving feedback from the community. Therefore DappRadar expanded the feature from Ethereum to also include Polygon, Tron and BNB Chain. Catered towards Web3 professionals, the Wallet Interaction Labels are only visible to DappRadar PRO members.
When a dapp uses various chains, it will only show Wallet Interaction Labels for the supported blockchain ecosystems: Ethereum, Polygon, BNB Chain and Tron.
Wallet Interaction Labels allow analysts to see what type of wallets interact with a dapp. This means that investors can see whether the wallets are actually active users, bots or maybe whales.
Depending on the dapp and its onboarding mechanisms, the Wallet Interaction Labels can help you to better understand the community. Try the dapp by clicking “Open Dapp” on the product page, and see how new users are being welcomed. Whether the dapp creates new wallets in the background, or uses MetaMask to connect an existing wallet, can make a lot of difference.
Wallet Interaction Labels allow users to see what types of wallets regularly interact with a dapp. This means that not only does a dapp product page on DappRadar provide valuable blockchain metrics, it now also provides a context. Users can see what types of wallets interact with a dapp, which would in turn give them a reason to engage or interact with a dapp and its community.
Through the use of AI, DappRadar uses Wallet Interaction Labels to identify the amount of human and bot activity within an ecosystem. Simply said, the AI defines wallet activity within a dapp's ecosystem into 3 potential categories:
- 1.🧑💻 = Likely Human
- 2.🤖 = Likely Bot
- 3.🥷 = Mixed
The behavior of the Mixed wallets can be quite varied, and requires deeper analysis to determine whether these are operated by a human or a bot. These could for example be wallets to buy and sell high quantities of cryptocurrencies, and such whale activity can be both bot and human behavior, or maybe even a mix of both.
DappRadar first creates a model. To do this, we collect all wallet and transactional data for an ecosystem, and segment all those broadly into 2 categories: interesting and uninteresting. Then we apply behavioral labels to the interesting wallets, and we repeat the process in order to define labels and sublabels.
After defining the model and the rules for the labels, we can update the data and apply the defined labels to the new data. The AI will only apply labels to wallets that fit the model which has been created.
Within the blockchain space wallets are used for all kinds of purposes. But by looking at certain behavioral patterns, it's possible to place them into a bucket and label them.
People who have rarely interacted with a particular dapp in recent times.
Wallets or Accounts that have been inactive for an extended period of time. These wallets are dormant either by choice, or because someone lost access to them.
These users trade based on short-term opportunities rather than long-term investment. They 'flip' assets for a quick gain, and jump on trends for profit.
These users or wallets regularly interact with a dapp, while pushing high-value transactions.
These users or wallets regularly interact with a dapp, while pushing low-value transactions.
Users who interact with the dapp or wallet as part of their daily routine.
Users or wallets which are very active and proficient in using a certain dapp.
Accounts or wallets that show behavior consistent with automated processes or bots, for example interacting with dapps on a schedule.
Wallets that primarily send funds out. This could for example be a wallet that distributes rewards or airdrops.
Wallets that primarily receive funds. For example, users claiming earnings, rewards and other payouts.