[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-560485-105":3,"detail-sidebar-cat-1-en-105":80,"doc-detail-560485-en":126},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":73,"head_meta":75,"extra_data":77,"updated_unix":79},105,"en","quantitative-analysis-of-the-full-bitcoin-transaction-graph-paper","Quantitative Analysis of the Full Bitcoin Transaction Graph - paper","","Quantitative analysis is applied to the complete Bitcoin transaction history, focusing on how account owners behave in acquiring, spending, and reallocating Bitcoins. Using the publicly accessible transaction records, the work constructs and refines a transaction graph by identifying cases where multiple addresses correspond to the same owner and merging them. The study summarizes key statistical distributions and isolates large transactions, revealing that most major transfers trace back to a single November 2010 event.",{"@graph":14,"@context":72},[15,34,55],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/template/","Template",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/template/general/","General",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/template/quantitative-analysis-of-the-full-bitcoin-transaction-graph-paper/560485/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/quantitative-analysis-of-the-full-bitcoin-transaction-graph-paper/560485.png","ImageObject",442,249,{"name":42,"@type":43},"eBook King","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-21","2026-10-12",true,{"@type":52,"interactionType":53,"userInteractionCount":33},"InteractionCounter",{"@type":54},"ViewAction",{"@type":56,"mainEntity":57},"FAQPage",[58,64,68],{"name":59,"@type":60,"acceptedAnswer":61},"What data and method are used to analyze the Bitcoin transaction graph?","Question",{"text":62,"@type":63},"The analysis downloads the full public transaction history and builds a graph of Bitcoin addresses and transactions. It merges addresses that can be shown to belong to the same owner to produce a more accurate graph.","Answer",{"name":65,"@type":60,"acceptedAnswer":66},"What kinds of behavioral questions does the paper address?",{"text":67,"@type":63},"It investigates typical behavior of account owners, including how they acquire and spend Bitcoins, how balances vary over time, and how Bitcoins move among accounts.",{"name":69,"@type":60,"acceptedAnswer":70},"What does the paper find about large transactions?",{"text":71,"@type":63},"It isolates transactions above a specified large threshold and finds that nearly all large transactions are connected as descendants of a single large transaction from November 2010, with complex chain and fork-merge structures.","https://schema.org",{"og:url":32,"og:type":74,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":76,"canonical":32},"index,follow",{"doc_id":78,"site_id":7},560485,1792172090,{"code":4,"msg":81,"data":82},"success",[83,88,93,98,103,108,113,118,123],{"id":84,"doc_module":22,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},11,"Presentations",90,"presentations",{"id":89,"doc_module":22,"doc_module_name":25,"category_name":90,"show_sort_weight":91,"slug":92},12,"Resumes",80,"resumes",{"id":94,"doc_module":22,"doc_module_name":25,"category_name":95,"show_sort_weight":96,"slug":97},14,"Invoices",70,"invoices",{"id":99,"doc_module":22,"doc_module_name":25,"category_name":100,"show_sort_weight":101,"slug":102},15,"Posters",60,"posters",{"id":104,"doc_module":22,"doc_module_name":25,"category_name":105,"show_sort_weight":106,"slug":107},16,"Social Media",50,"social-media",{"id":109,"doc_module":22,"doc_module_name":25,"category_name":110,"show_sort_weight":111,"slug":112},17,"Forms",40,"forms",{"id":114,"doc_module":22,"doc_module_name":25,"category_name":115,"show_sort_weight":116,"slug":117},18,"Letters",30,"letters",{"id":119,"doc_module":22,"doc_module_name":25,"category_name":120,"show_sort_weight":121,"slug":122},21,"Paper Templates",5,"papers-templates",{"id":124,"doc_module":22,"doc_module_name":25,"category_name":29,"show_sort_weight":4,"slug":125},158,"general-158",{"code":4,"msg":81,"data":127},{"doc_id":78,"user_id":128,"nickname":42,"user_avatar":129,"doc_module":22,"category_id":124,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":130,"file_id":131,"file_url":132,"file_type":133,"file_size":134,"view_count":33,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":114,"language":135,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":136,"faqs":137,"seo_title":138,"seo_description":12,"update_tm":139,"read_time":140},962088006270,"https://ap-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45","Quantitative Analysis of the Full Bitcoin Transaction Graph  \nDorit Ron and Adi Shamir  \nDepartment of Computer Science and Applied Mathematics, The Weizmann Institute of Science, Israel  \n{dorit .ron, [adi.shamir}@weizmann.ac.il](adi.shamir}@weizmann.ac.il)  \nAbstract. The Bitcoin scheme is a rare example of a large scale global payment system in which all the transactions are publicly accessible (but in an anonymous way) . We downloaded the full history of this scheme, and analyzed many statistical properties of its associated transaction graph. In this paper we answer for the 􀀌rst time a variety of interesting questions about the typical behavior of account owners, how they acquire and how they spend their Bitcoins, the balance of Bitcoins they keep in their accounts, and how they move Bitcoins between their various accounts in order to better protect their privacy. In addition, we isolated all the large transactions in the system, and discovered that almost all of them are closely related to a single large transaction that took place in November 2010, even though the associated users apparently tried to hide this fact with many strange looking long chains and fork-merge structures in the transaction graph.  \nKeywords: Bitcoin, digital coins, electronic cash, payment systems, transaction graphs, quantitative analysis  \n1 Introduction  \nBitcoins are digital coins which are not issued by any government, bank, or organization, and rely on cryptographic protocols and a distributed network of users to mint, store, and transfer. The scheme was 􀀌rst suggested in 2008 by Satoshi Nakamoto [1], and became fully operational in January 2009 . It had attracted a large number of users and a lot of media attention [2] [3] [4], but so far it was di􀀎cult to get precise answers to simple questions such as: How many di􀀋erent users are there in the system? How many Bitcoins are typically kept in each account, and how does this balance vary over time? Are most Bitcoins kept by a few large users? Do they keep their Bitcoins in \\saving accounts\" ordo they spend them immediately? How many users had large balances at some point in time? What is the size distribution of Bitcoin transactions, and how many of them are micropayments?  \nIn this paper we answer all these (and many additional) questions. We use the fact that all the transactions ever carried out in the Bitcoin system are available on the internet (in an anonymous way) . On May 13th 2012 we downloaded  \n2 Dorit Ron, Adi Shamir  \nthe full public record of this system, which consisted of about 180,000 HTML 􀀌les. After parsing and processing these 􀀌les, we built a graph of all the Bitcoin addresses and transactions up to that date. We then used the intrinsic properties of the scheme in order to identify many cases in which we can show that di􀀋erent addresses must belong to the same owner, and used this information to contract the transaction graph by merging such addresses, in order to get a more accurate picture of the full 􀀌nancial activity of all the owners. After obtaining this new graph, we analyzed many of its statistical properties. In this paper we describe the most interesting and informative distributions we found in a series of tables. In addition, we isolated all the large (􀀕 50 ; 000 Bitcoins) transactions which were ever recorded in the system, and analyzed how these amounts were accumulated and then spent. We discovered that almost all these large transactions were the descendants of a single large transaction involving 90,000 Bitcoins which took place on November 8th 2010, and that the subgraph of these transactions contains many strange looking chains and fork-merge structures, in which a large balance is either transferred within a few hours through hundreds of temporary intermediate accounts, or split into many small amounts which are sent to di􀀋erent accounts only in order to be recombined shortly afterwards into essentially the same amount in a new account.  \nThere was on","cbCailRQYsu7lTZx","https://ap.wps.com/l/cbCailRQYsu7lTZx","pdf",1847409,"English","# Introduction\n# The Bitcoin Network","[{\"question\":\"What data and method are used to analyze the Bitcoin transaction graph?\",\"answer\":\"The analysis downloads the full public transaction history and builds a graph of Bitcoin addresses and transactions. It merges addresses that can be shown to belong to the same owner to produce a more accurate graph.\"},{\"question\":\"What kinds of behavioral questions does the paper address?\",\"answer\":\"It investigates typical behavior of account owners, including how they acquire and spend Bitcoins, how balances vary over time, and how Bitcoins move among accounts.\"},{\"question\":\"What does the paper find about large transactions?\",\"answer\":\"It isolates transactions above a specified large threshold and finds that nearly all large transactions are connected as descendants of a single large transaction from November 2010, with complex chain and fork-merge structures.\"}]","Quantitative Analysis of the Full Bitcoin Transaction Graph - paper | PDF",1791803221,6]