Keeping Pace With the Evolution of Illicit Darknet Fentanyl Markets: Using a Mixed Methods Approach to Identify Trust Signals and Develop a Vendor Trustworthiness Index

Abstract

Illicit darknet markets (DNMs) are highly uncertain and in a perpetual state of flux. These markets thrive in a zero-trust, high-risk environment. However, the trustworthiness of vendors plays a critical role in illicit transactions and the sustainability of the illegal trade of goods and services on DNMs. Focusing on the illicit fentanyl trade and applying signaling theory and embedded mixed methods design, we examined different ways that trustworthiness is signaled by vendors on darknet sites. Fentanyl, a synthetic opioid, in recent years, has been declared a public health emergency in the United States due to its high potency and unprecedented number of deaths associated with its use; however, the topic remains understudied and requires urgent attention. There are few studies that have focused on fentanyl trafficking on DNMs and no mixed method studies that have focused specifically on trust signals in DNM fentanyl networks. In our research, first, we conducted a focus group and in-depth interviews with criminal justice professionals to understand the inner workings of darknet sites, fentanyl networks, and how trust is assessed. Second, we scraped select darknet sites to collect and curate scraped data for later examination of vendor trustworthiness on DNMs. Third, using signaling theory to understand how vendors signal trustworthiness on select darknet sites selling drugs, including fentanyl, we applied both qualitative and quantitative content analysis of DNM features, and language used in vendor profiles, listings, and product/vendor reviews, to inform the development of a trustworthiness index. In this research, we used software, such as Atlas.ti and Python, to analyze our data. The main purpose of this article is to provide an in-depth description of the mixed methods approach we used to inform the development of a vendor trustworthiness index, which we used to examine trust between illicit fentanyl vendors and buyers. Our research can serve as a guide for the development of DNM vendor trustworthiness index for future research on other illegal markets.