How centralized is decentralized? Comparison of wealth distribution in coins and tokens
Rapidly growing distributed ledger technologies (DLTs) have recently received attention among researchers in both industry and academia. While a lot of existing analysis (mainly) of the Bitcoin and Ethereum networks is available, the lack of measurements for other crypto projects is observed. This a...
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| creator | Kuśmierz, Bartosz Overko, Roman |
| description | Rapidly growing distributed ledger technologies (DLTs) have recently received
attention among researchers in both industry and academia. While a lot of
existing analysis (mainly) of the Bitcoin and Ethereum networks is available,
the lack of measurements for other crypto projects is observed. This article
addresses questions about tokenomics and wealth distributions in
cryptocurrencies. We analyze the time-dependent statistical properties of top
cryptocurrency holders for 14 different distributed ledger projects. The
provided metrics include approximated Zipf coefficient, Shannon entropy, Gini
coefficient, and Nakamoto coefficient. We show that there are quantitative
differences between the coins (cryptocurrencies operating on their own
independent network) and tokens (which operate on top of a smart contract
platform). Presented results show that coins and tokens have different values
of approximated Zipf coefficient and centralization levels. This work is
relevant for DLTs as it might be useful in modeling and improving the committee
selection process, especially in decentralized autonomous organizations (DAOs)
and delegated proof of stake (DPoS) blockchains. |
| doi_str_mv | 10.48550/arxiv.2207.01340 |
| format | Article |
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attention among researchers in both industry and academia. While a lot of
existing analysis (mainly) of the Bitcoin and Ethereum networks is available,
the lack of measurements for other crypto projects is observed. This article
addresses questions about tokenomics and wealth distributions in
cryptocurrencies. We analyze the time-dependent statistical properties of top
cryptocurrency holders for 14 different distributed ledger projects. The
provided metrics include approximated Zipf coefficient, Shannon entropy, Gini
coefficient, and Nakamoto coefficient. We show that there are quantitative
differences between the coins (cryptocurrencies operating on their own
independent network) and tokens (which operate on top of a smart contract
platform). Presented results show that coins and tokens have different values
of approximated Zipf coefficient and centralization levels. This work is
relevant for DLTs as it might be useful in modeling and improving the committee
selection process, especially in decentralized autonomous organizations (DAOs)
and delegated proof of stake (DPoS) blockchains.</description><identifier>DOI: 10.48550/arxiv.2207.01340</identifier><language>eng</language><subject>Computer Science - Distributed, Parallel, and Cluster Computing</subject><creationdate>2022-07</creationdate><rights>http://creativecommons.org/licenses/by/4.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2207.01340$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2207.01340$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Kuśmierz, Bartosz</creatorcontrib><creatorcontrib>Overko, Roman</creatorcontrib><title>How centralized is decentralized? Comparison of wealth distribution in coins and tokens</title><description>Rapidly growing distributed ledger technologies (DLTs) have recently received
attention among researchers in both industry and academia. While a lot of
existing analysis (mainly) of the Bitcoin and Ethereum networks is available,
the lack of measurements for other crypto projects is observed. This article
addresses questions about tokenomics and wealth distributions in
cryptocurrencies. We analyze the time-dependent statistical properties of top
cryptocurrency holders for 14 different distributed ledger projects. The
provided metrics include approximated Zipf coefficient, Shannon entropy, Gini
coefficient, and Nakamoto coefficient. We show that there are quantitative
differences between the coins (cryptocurrencies operating on their own
independent network) and tokens (which operate on top of a smart contract
platform). Presented results show that coins and tokens have different values
of approximated Zipf coefficient and centralization levels. This work is
relevant for DLTs as it might be useful in modeling and improving the committee
selection process, especially in decentralized autonomous organizations (DAOs)
and delegated proof of stake (DPoS) blockchains.</description><subject>Computer Science - Distributed, Parallel, and Cluster Computing</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNpNj71OwzAURr0woMIDMOEXSPBPcm1PFYqAIlViqcQYXceOsJralR0o8PTQwtDh0yed4UiHkBvO6ka3LbvD_Bk-aiGYqhmXDbskr6t0oIOPc8YpfHtHQ6HOn4El7dJujzmUFGka6cHjNL9RF8qcg32fwy8OkQ4pxEIxOjqnrY_lilyMOBV__f8Lsnl82HSrav3y9NzdrysExSrNlTAAUjTWNYDKc-Vb5dXAHcAo7XHaGj0AGGuYFtwACrCIXknHQS7I7Z_2VNbvc9hh_uqPhf2pUP4A705MOg</recordid><startdate>20220704</startdate><enddate>20220704</enddate><creator>Kuśmierz, Bartosz</creator><creator>Overko, Roman</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20220704</creationdate><title>How centralized is decentralized? Comparison of wealth distribution in coins and tokens</title><author>Kuśmierz, Bartosz ; Overko, Roman</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a670-8172966324bd46a7e17e57e7c1d66f3b6f3b8b98c669b9082196a26baae73d163</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Computer Science - Distributed, Parallel, and Cluster Computing</topic><toplevel>online_resources</toplevel><creatorcontrib>Kuśmierz, Bartosz</creatorcontrib><creatorcontrib>Overko, Roman</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Kuśmierz, Bartosz</au><au>Overko, Roman</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>How centralized is decentralized? Comparison of wealth distribution in coins and tokens</atitle><date>2022-07-04</date><risdate>2022</risdate><abstract>Rapidly growing distributed ledger technologies (DLTs) have recently received
attention among researchers in both industry and academia. While a lot of
existing analysis (mainly) of the Bitcoin and Ethereum networks is available,
the lack of measurements for other crypto projects is observed. This article
addresses questions about tokenomics and wealth distributions in
cryptocurrencies. We analyze the time-dependent statistical properties of top
cryptocurrency holders for 14 different distributed ledger projects. The
provided metrics include approximated Zipf coefficient, Shannon entropy, Gini
coefficient, and Nakamoto coefficient. We show that there are quantitative
differences between the coins (cryptocurrencies operating on their own
independent network) and tokens (which operate on top of a smart contract
platform). Presented results show that coins and tokens have different values
of approximated Zipf coefficient and centralization levels. This work is
relevant for DLTs as it might be useful in modeling and improving the committee
selection process, especially in decentralized autonomous organizations (DAOs)
and delegated proof of stake (DPoS) blockchains.</abstract><doi>10.48550/arxiv.2207.01340</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Computer Science - Distributed, Parallel, and Cluster Computing |
| title | How centralized is decentralized? Comparison of wealth distribution in coins and tokens |
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