Dark Web Activity in the Japanese Language Between 2004 and 2020

A Case Study of the Onion Channel

Bibliographic Data

ID2153742
AuthorsNaoki Hiramoto (0000-0001-7021-3608, Mercari/Mercoin, Tokyo, Japan), Yoichi Tsuchiya (0000-0003-2485-3959, Meiji University, Tokyo, Japan, corresponding author)
Year2024
Volume45
Issue11
Pages1550-1567
Publication date2024-11-01
Open AccessYes
TypeARTICLE
VenueDeviant Behavior (JOURNAL)
Journal identifiersISSN: 0163-9625 • E-ISSN: 1521-0456
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/01639625.2024.2311751
OpenAlexW4391446215
LanguageEN
Citations received1
References cited32

This paper investigates the activity of Japanese-language dark web sites by examining a Japanese dark web forum, the Onion Channel. While global crypto markets and English-language forums have been extensively studied, there has been little research on Japanese-language dark web sites. The number of posts and the variety of activities on the Onion Channel started increasing around mid-2012, exhibited steady growth until the end of 2016, and then showed a declining trend toward mid-2020. This study classifies activities on the forum into 10 categories. The forum was dominated by illegal and unethical activity. In particular, illegal drug dealing and cyberbullying were the two major illegal and unethical activities that took place there. The large presence of drug-related activity suggests that the forum on the dark web operated as a substitute for crypto markets. Textual analysis revealed that cannabis and methamphetamine were two major drugs that were likely to be sold, and those deals were likely to be completed face-to-face at a designated location. There was also a certain amount of illegal content, such as information related to fraud, identity theft and sales of false IDs, and hacking, as well as criminal conversations

Channel (broadcasting · Telecommunications · World Wide Web · Computer Science · Hate Speech and Cyberbullying Detection · Internet Traffic Analysis and Secure E-voting · Psychology · Spam and Phishing Detection

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