Cambridge University Launches A Bitcoin Mining Tracking Tool

A designated team at Cambridge University has just released The Bitcoin Mining Map. The digital tool shows the geographical location of Bitcoin hash rate distribution and the countries where it’s concentrated.

The Bigger Picture

The tracking tool enables users to locate and keep an eye on the monthly share of the global hash rate of different countries, starting from September 2019. The bitcoin tracker will also provide users with an additional second map consisting of focused, detailed and in-depth information and comparison of Chinese provinces.

Altogether the tool shows China’s position with more than 65% on the global ranking scale. Far behind is the United States with 7.24%, Russia with 6.90%, Kazakhstan with 6.17%, Malaysia with 4.33%, and Iran with 3.82%.

The Cambridge Centre for Alternative Finance (CCAF), situated at the Cambridge Judge Business School, has been developing the digital tool for the last year.

Based On IP Addresses

The Bitcoin mining map is based on geo-location info (i.e., IP addresses) of hashers that are connected to the mining pools, Poolin, and ViaBTC. As the report reads, all of the mentioned pools have personally agreed to share the necessary aggregate-level data for research purposes and the bitcoin mining’s sake. These pools represent an estimated 37% of the Bitcoin total hash rate collectively during the regarded period of tracking.

As the report reads, many miners in certain regions tend to mask their IP addresses, using VPNs or proxy services – a common practice, which makes their location harder to specify. Specialists in CCAF point out that such activity is capable of distorting the overall geographic distribution and could end up in an overestimation of hash rate in some regions and countries.

Suchlike behavior was highly notable in the Chinese province of Zhejiang, as the report states. To minimize this effect, Cambridge’s bitcoin tracking tool divides the Zhejiang’s hash rate proportionally among other Chinese provinces, which are listed in the pool’s dataset.

Featured Image Courtesy of Telegraph

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