Publications

Hidden Hate: Analysis of Hate Speech on a Darknet Forum

Kenji LogieNoah CohenKatrina PerryE. Taylor

Research relating to hate speech and the darknet have both grown significantly in the previous decade. Nonetheless, there is a dearth of empirical research exploring how hate speech manifests within the darknet, the groups targeted. This study seeks to fill this gap in the literature by investigating the different targets of hate speech within the darknet forum Dread and how posts within this forum are affected by hate motivated events.

Full Abstract

Through analysis of posts (n = 1,047) 3 months before and after major hate-motivated events, this study finds that approximately 13% (n =135) of posts in our sample contain hate speech targeting several groups. In addition we also examined the variations in targets between forum-specific subjects (internal) and targets outside of the forum (external). Our findings suggest that there is limited conversation surrounding hate-motivated events discussed in mainstream media on Dread. However, instances of hate speech, predominantly targeting religious, racial, and gender-related groups, are present at a lower percentage in comparison to research conducted about hate speech on social media platforms.

Logie, K., Cohen, N. D., Taylor, E., & Perry, K. (2025). Hidden Hate: Analysis of Hate Speech on a Darknet Forum. Justice Quarterly, 1–24. https://doi.org/10.1080/07418825.2025.2501544

The article can be found here: https://doi.org/10.1080/07418825.2025.2501544

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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

Marie-Helen MarasJana ArsovskaAdam Scott WandtKenji Logie

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.

Full Abstract

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.

Maras, M.-H., Arsovska, J., Wandt, A. S., & Logie, K. (2023). 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. Journal of Contemporary Criminal Justice, 39(2), 276-297. https://doi-org.ez.lib.jjay.cuny.edu/10.1177/10439862231159530 (Original work published 2023)

This article can be found here: https://doi-org.ez.lib.jjay.cuny.edu/10.1177/10439862231159530

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The Bull and Millionaire Mike: A Look at Darknet and Securities Fraud

Jana ArsovskaKenji LogieMarie-Helen Maras

Criminals have long leveraged information and communications technology to commit crimes that pose significant threats to public safety, economic security, and national security. Illegal goods and services are marketed on websites accessible through traditional search engines (i.e., clearnet) and non-indexed websites that cannot be identified and accessed through traditional clearnet search engines such as Google or Bing (i.e., Deep Web). The Deep Web, which includes Intranets, websites that are password-protected, and websites accessible only using specialized browsers (e.g., Tor, “The Onion Router”), are part of what is known as the Dark Web. Within the Dark Web, the term darknet has been used to describe spaces used to facilitate criminal activities, such as the trade of illicit goods and services.

https://www.asisonline.org/security-management-magazine/latest-news/online-exclusives/2022/the-bull-and-millionaire-mike-a-look-at-darknet-and-securities-fraud–summary/

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The SECI model and darknet markets: Knowledge creation in criminal organizations and communities of practice

Marie-Helen MarasJana ArsovskaAdam Scott WandtKenji LogieMelanie Knieps

This study examines darknet markets through the lens of a business theory on knowledge management. Taking epistemological and ontological dimensions into consideration, this study uses Nonaka’s (1991) SECI model as a theoretical framework to identify and describe how tacit and explicit knowledge is created and shared on Silk Road, Pandora and Agora darknet markets, and how people affect this process. By studying this process, insights can be obtained into darknet market criminal organizations and communities of practice and their impact on the continuity and resilience of illicit darknet markets.

Full Abstract

This project used data from the Internet Archive collection of publicly available darknet market scrapes between 2011 and 2015 from Branwen et al. (2015). We observed instances of the SECI model (socialization, externalization, combination, and internalization) on darknet markets in both criminal organizations and communities of practice. Darknet market leaders and groups facilitated both knowledge creation and sharing. This study is the first to test the SECI model on darknet markets. The study provides an understanding of the complexity and resilience of darknet markets, as well as valuable information to help guide law enforcement agencies efforts to stop the illicit trade of goods and services.

Maras, M.-H., Arsovska, J., Wandt, A. S., Knieps, M., & Logie, K. (2024). The SECI model and darknet markets: Knowledge creation in criminal organizations and communities of practice. European Journal of Criminology, 21(2), 165-190. https://doi.org/10.1177/14773708221115167

The article can be found here: https://journals.sagepub.com/doi/10.1177/14773708221115167

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Decoding hidden darknet networks: What we learned about the illicit fentanyl trade on Alphabay

Decoding hidden darknet networks: What we learned about the illicit fentanyl trade on Alphabay

Marie-Helen MarasKenji LogieAdam Scott WandtBryce BarthulyJana Arsovska

Using the AlphaBay DNM as a case study, we conducted mixed methods qualitative research. We scraped and analyzed data from the AlphaBay I2P website using, among other methods, content and social network analysis, to uncover hidden fentanyl networks.

Full Abstract

The opioid epidemic, impacted from the proliferation of fentanyl, has added impetus to the need to detect fentanyl, sources of fentanyl, and places where fentanyl and drugs adulterated with fentanyl are available. Many darknet marketplaces (DNMs) have rules that ban fentanyl. However, it is unclear how these affect the fentanyl market. Using the AlphaBay DNM as a case study, we conducted mixed methods qualitative research. We scraped and analyzed data from the AlphaBay I2P website using, among other methods, content and social network analysis, to uncover hidden fentanyl networks.Our research highlights the next evolution of darknet marketplaces– the migration of DNMs from Tor to I2P and the methods that can be used identify fentanyl networks, irrespective of where sites are: I2P, Tor, or multihomed on I2P andTor. Despite its ban in the Global AlphaBay Rules, our research revealed the sale of fentanyl on the AlphaBay DNM. Unlike previous studies, our findings predominantly revealed the covert sale of fentanyl on AlphaBay and predatory vendors selling illicit drugs, which unbeknownst to buyers, contained fentanyl. To a lesser extent, our findings identified the overt sale of fentanyl patches on AlphaBay. Although we examined only one DNM, the prevalence of the covert sale of fentanyl and the presence of predatory vendors underscores the importance of research that decodes the language of vendors who surreptitiously sell fentanyl or drugs adulterated with fentanyl or other illicit substances. The results of our research can inform strategies aimed at disrupting and dismantling DNM fentanyl networks.

Maras M-H, Logie K, Arsovska J, Wandt AS, Barthuly B. Decoding hidden darknet networks:What we learned about the illicit fentanyl trade on AlphaBay. J Forensic Sci. 2023;68:1451–69. https://doi.org/10.1111/1556-4029.15341

The article can be found here: https://onlinelibrary.wiley.com/share/author/BS2FPUJXQMJICXGWM4HF?target=10.1111/1556-4029.15341

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Understanding the Intersection between Technology and Kidnapping: A Typology of Virtual Kidnapping

Understanding the Intersection between Technology and Kidnapping: A Typology of Virtual Kidnapping

Marie-Helen MarasJana Arsovska

No longer limited by geographic locations and in-person interactions, criminals have leveraged information and communication technology to commit virtual kidnappings. In its simplest form, a virtual kidnapping is a cyber-enabled crime where criminals contact targets (falsely) claiming to have kidnapped a significant other, child, or other relative and threatening to cause death or serious bodily harm to the person unless a ransom is paid.

Funding Source

Faculty Scholarship grant, Office for the Advancement of Research at John Jay College

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[virtual kidnapping]