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Rapidly growing distributed ledger technologies (DLTs) have recently receivedattention among researchers in both industry and academia. While a lot ofexisting analysis (mainly) of the Bitcoin and Ethereum networks is available,the lack of measurements for other crypto projects is observed. This articleaddresses questions about tokenomics and wealth distributions incryptocurrencies. We analyze the time-dependent statistical properties of topcryptocurrency holders for 14 different distributed ledger projects. Theprovided metrics include approximated Zipf coefficient, Shannon entropy, Ginicoefficient, and Nakamoto coefficient. We show that there are quantitativedifferences between the coins (cryptocurrencies operating on their ownindependent network) and tokens (which operate on top of a smart contractplatform). Presented results show that coins and tokens have different valuesof approximated Zipf coefficient and centralization levels. This work isrelevant for DLTs as it might be useful in modeling and improving the committeeselection process, especially in decentralized autonomous organizations (DAOs)and delegated proof of stake (DPoS) blockchains.

How centralized is decentralized? Comparison of wealth distribution in coins and tokens