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Drug cryptomarkets increase information available to market actors, which should reduce information asymmetry and increase market efficiency. This study aims to determine whether cryptomarket listings accurately represent the advertised substance, weight or number and purity, and whether there are differences in products purchased from the same listing multiple times.

Law enforcement drug purchases – predominantly cocaine, methamphetamine, MDMA and heroin – from Australian cryptomarket vendors (n = 38 in 2016/2017) were chemically analysed and matched with cryptomarket listings (n = 23). Descriptive and comparative analyses were conducted.

Almost all samples contained the advertised substance. In most of these cases, drugs were either supplied as-advertised-weight or number, or overweight or number. All listings that quantified purity overestimated the actual purity. There was no consistent relationship between advertised purity terms and actual purity. Across the six listings purchased from multiple times, repeat purchases from the same listing varied in purity, sometimes drastically, with wide variation detected on listings purchased from only one month apart.

In this data set, cryptomarket listings were mostly accurate, but the system was far from perfect, with purity overestimated. A newer, larger, globally representative sample should be obtained to test the applicability of these findings to currently operating cryptomarkets.

This paper reports on the largest data set of forensic analysis of drug samples obtained from cryptomarkets, where data about advertised drug strength/dose were obtained.

The purpose of this paper is to map research communities related to heroin-assisted treatment (HAT) and the scientific network they are part of to determine their structure and content.

Co-authorship as the basis for conducting social network analysis with regard to degree, weighted degree, betweenness centrality, and edge betweenness centrality.

A number of central researchers were identified on the basis of the number of their collaborative relations. Central actors were also identified on the basis of their position in the research network. In total, 11 research communities were constructed with different scientific content. HAT research communities are closely connected to medical, psychiatric, and epidemiological research and very loosely connected to social research.

The first mapping of the collaborative network HAT researchers using social network methodology.