I'd like to know how they get those numbers.
This research
https://www.rand.org/pubs/research_reports/RR4418.html581,871 listings across these eight marketplaces. If they picked right marketplaces and how accurate is this is beyond my knowledge. Research was "made" by Zcash most likely to show how little it is used on dark markets. They have plenty of money to waste on such things. But reality is that it is used just the same little as everywhere else.
Looks like a load of shit wrapped up all in a bowtie to me.thanks for the link.
43Annex A. MethodologyA.1. Overview of approachThis study had two overarching research tasks, as shown in Table A.1. The following sections within this annex provide further information on each task, as well as underlying assumptions and limitations.Table A.1 Overview of approachResearch taskResearch approachTask 1: Identify the nature and scale of Zcash usage on dark web marketsUse the RAND Dark Web Observatory (DWO) to extract the number of markets and vendors accepting Zcash as form of payments. Task 2: Examine other illicit uses of Zcash Conduct literature review and key informant interviews.A.1.1. Task 1: Identify the nature and scale of Zcash usage on dark web marketsTask 1 of this study entailed the primary exploration of which cryptocurrencies are most commonly accepted and used on dark web markets. The main purpose of this task was to gather and assess the available evidence regarding to what extent dark web marketplaces accept Zcash and how this compares to other cryptocurrencies. This was done using the tools of the RAND Dark Web Observatory (DWO). The DWO aggregates listing descriptions into a single text-formatted field, which is often used by vendors to communicate their accepted methods of payment. The research team began by using ‘mentions’ of select cryptocurrencies in these description fields as a proxy for ‘accepted methods of payment’. For these purposes, a mention can be defined as a case-insensitive, whole-word match on the text content. As an example, consider the text ‘Methamphetamine’. While it contains the correct letter sequence, E-T-H, a common abbreviation for the Ethereum cryptocurrency, it is not a whole-word match. On the other hand, the text ‘bitcoin, eth, monero, cc’ is a whole-word and case-insensitive match for ETH. Additionally, the term ‘unique’ was used to describe a single listing with a unique ‘Offer ID’ field, of which there may be multiple observations. This typically occurs after multiple web scraping sessions where the same listing is re-scraped. These kinds of duplicate listings are treated collectively as a single listing and therefore counted only once. This study focused exclusively on a listing’s ‘description’ field. For example, for a listing titled ‘250.000 Fullz records from Hospital’ (presumably a dump of hacked hospital data), the description is shown in Box 3. The relevant cryptocurrency information that matches the search criteria has been highlighted. Note that, although additional cryptocurrency information (e.g. ccbtc, lbc) may be provided by the vendor, this is not detected by this search approach
https://www.rand.org/content/dam/rand/pubs/research_reports/RR4400/RR4418/RAND_RR4418.pdf