  Due to the widespread use of smart contracts, Ethereum has become the
second-largest blockchain platform after Bitcoin. Many different types of
Ethereum accounts (ICO, Mining, Gambling, etc.) also have quite active trading
activities on Ethereum. Studying the transaction records of these specific
Ethereum accounts is very important for understanding their particular
transaction characteristics, and further labeling the pseudonymous accounts.
However, traditional methods are generally based on static and global
transaction networks to conduct research, ignoring useful information about
dynamic changes. Our work chooses six kinds of important account labels, and
builds ego networks for each kind of Ethereum account. We focus on the
interaction between the target node and neighbor nodes with temporal analysis.
Experiments show that there is a significant difference between various types
of accounts in terms of several network features, helping us better understand
their transaction patterns. To the best of our knowledge, this is the first
work to analyze the dynamic characteristics of Ethereum labeled accounts from
the perspective of transaction ego networks.
