Cebulka (Polish dark web cryptomarket and image board) messages data

General Information 1. Title of Dataset Cebulka (Polish dark web cryptomarket and image board) messages data. 2. Data Collectors Haitao Shi (The University of Edinburgh, UK); Patrycja Cheba (Jagiellonian University); Leszek Świeca (Kazimierz Wielki University in Bydgoszcz, Poland). 3. Funding Information The dataset is part of the research supported by the Polish National Science Centre (Narodowe Centrum Nauki) grant 2021/43/B/HS6/00710. Project title: “Rhizomatic networks, circulation of meanings and contents, and offline contexts of online drug trade” (2022-2025; PLN 956 620; funding institution: Polish National Science Centre [NCN], call: OPUS 22; Principal Investigator: Piotr Siuda [Kazimierz Wielki University in Bydgoszcz, Poland]). Data Collection Context 4. Data Source Polish dark web cryptomarket and image board called Cebulka (http://cebulka7uxchnbpvmqapg5pfos4ngaxglsktzvha7a5rigndghvadeyd.onion/index.php). 5. Purpose This dataset was developed within the abovementioned project. The project focuses on studying internet behavior concerning disruptive actions, particularly emphasizing the online narcotics market in Poland. The research seeks to (1) investigate how the open internet, including social media, is used in the drug trade; (2) outline the significance of darknet platforms in the distribution of drugs; and (3) explore the complex exchange of content related to the drug trade between the surface web and the darknet, along with understanding meanings constructed within the drug subculture. Within this context, Cebulka is identified as a critical digital venue in Poland’s dark web illicit substances scene. Besides serving as a marketplace, it plays a crucial role in shaping the narratives and discussions prevalent in the drug subculture. The dataset has proved to be a valuable tool for performing the analyses needed to achieve the project’s objectives. Data Content 6. Data Description The data was collected in three periods, i.e., in January 2023, June 2023, and January 2024. The dataset comprises a sample of messages posted on Cebulka from its inception until January 2024 (including all the messages with drug advertisements). These messages include the initial posts that start each thread and the subsequent posts (replies) within those threads. The dataset is organized into two directories. The “cebulka_adverts” directory contains posts related to drug advertisements (both advertisements and comments). In contrast, the “cebulka_community” directory holds a sample of posts from other parts of the cryptomarket, i.e., those not related directly to trading drugs but rather focusing on discussing illicit substances. The dataset consists of 16,842 posts. 7. Data Cleaning, Processing, and Anonymization The data has been cleaned and processed using regular expressions in Python. Additionally, all personal information was removed through regular expressions. The data has been hashed to exclude all identifiers related to instant messaging apps and email addresses. Furthermore, all usernames appearing in messages have been eliminated. 8. File Formats and Variables/Fields The dataset consists of the following files: Zipped .txt files (“cebulka_adverts.zip” and “cebulka_community.zip”) containing all messages. These files are organized into individual directories that mirror the folder structure found on Cebulka. Two .csv files that list all the messages, including file names and the content of each post. The first .csv lists messages from “cebulka_adverts.zip,” and the second .csv lists messages from “cebulka_community.zip.” Ethical Considerations 9. Ethics Statement A set of data handling policies aimed at ensuring safety and ethics has been outlined in the following paper: Harviainen, J.T., Haasio, A., Ruokolainen, T., Hassan, L., Siuda, P., Hamari, J. (2021). Information Protection in Dark Web Drug Markets Research [in:] Proceedings of the 54th Hawaii International Conference on System Sciences, HICSS 2021, Grand Hyatt Kauai, Hawaii, USA, 4-8 January 2021, Maui, Hawaii, (ed.) Tung X. Bui, Honolulu, HI, pp. 4673-4680. The primary safeguard was the early-stage hashing of usernames and identifiers from the messages, utilizing automated systems for irreversible hashing. Recognizing that automatic name removal might not catch all identifiers, the data underwent manual review to ensure compliance with research ethics and thorough anonymization.数据集基本信息 1. 数据集名称 Cebulka（波兰暗网（dark web）加密货币市场（cryptomarket）与图像论坛（image board））留言数据集。 2. 数据采集者 史海涛（英国爱丁堡大学）；帕特丽夏·切巴（雅盖隆大学）；莱谢克·施维察（波兰比得哥什卡齐米日维尔基大学）。 3. 资助信息 本数据集隶属于波兰国家科学中心（Polish National Science Centre, Narodowe Centrum Nauki）资助的研究项目，项目编号为2021/43/B/HS6/00710。 项目名称为“根状网络、意义与内容流通，以及线上毒品交易的线下语境”（2022-2025年，资助金额956 620波兰兹罗提，资助机构：波兰国家科学中心[NCN]，资助计划：OPUS 22，项目负责人：彼得·希乌达，波兰比得哥什卡齐米日维尔基大学）。 数据采集背景 4. 数据来源 波兰暗网（dark web）加密货币市场（cryptomarket）与图像论坛（image board）Cebulka，访问地址为http://cebulka7uxchnbpvmqapg5pfos4ngaxglsktzvha7a5rigndghvadeyd.onion/index.php。 5. 研究目的 本数据集依托上述项目构建而成。该项目聚焦于与破坏性网络行为相关的互联网活动研究，尤其侧重波兰国内的线上毒品交易市场。本研究旨在达成三大目标：（1）探究开放互联网（含社交媒体）在毒品交易中的使用方式；（2）阐明暗网（darknet）平台在毒品分销环节中的重要性；（3）探索表层网（surface web）与暗网（darknet）之间围绕毒品交易的复杂内容交换模式，并解析毒品亚文化中构建的意义体系。 在此语境下，Cebulka被认定为波兰暗网（dark web）非法毒品交易场景中的关键数字阵地。该平台除承担交易市场功能外，还在塑造毒品亚文化的主流叙事与讨论方面发挥着核心作用。本数据集为实现项目研究目标所需的各类分析提供了宝贵支撑。 数据内容 6. 数据说明 本次数据采集分为三个阶段，分别为2023年1月、2023年6月及2024年1月。数据集涵盖自论坛创立至2024年1月期间发布在Cebulka上的留言样本（含所有毒品广告相关留言），包括各讨论串的初始发帖及后续回复留言。 数据集分为两个目录："cebulka_adverts"目录存储与毒品广告相关的帖子（含广告内容及评论）；"cebulka_community"目录则存储加密货币市场其他板块的留言样本，即未直接涉及毒品交易、仅围绕非法药物展开讨论的帖子。本数据集共计16842条留言。 7. 数据清理、处理与匿名化 本数据集通过Python正则表达式完成清理与处理流程。此外，所有个人信息均通过正则表达式予以移除；数据集已进行哈希处理，以剔除所有与即时通讯应用及电子邮箱地址相关的标识符；同时，留言中出现的所有用户名均已删除。 8. 文件格式与变量/字段 本数据集包含以下文件： - 两个压缩文本文件（"cebulka_adverts.zip"与"cebulka_community.zip"），存储全部留言。这些文件按照与Cebulka论坛一致的文件夹结构拆分为独立子目录。 - 两个CSV文件，分别列出所有留言及其文件名与单条帖子内容：其中第一个CSV文件对应"cebulka_adverts.zip"中的留言，第二个CSV文件对应"cebulka_community.zip"中的留言。 伦理考量 9. 伦理声明 本研究已制定一套旨在保障数据安全与伦理合规的处理规范，相关细节刊载于以下论文： Harviainen, J.T., Haasio, A., Ruokolainen, T., Hassan, L., Siuda, P., Hamari, J. (2021). 暗网毒品交易市场研究中的信息保护 [in:] 第54届夏威夷国际系统科学大会（HICSS 2021）论文集，会议地点：美国夏威夷考艾岛君悦酒店，2021年1月4日至8日，夏威夷毛伊岛，（编辑）Tung X. Bui，檀香山，HI，第4673-4680页。 本研究的核心保护措施为：对留言中的用户名与标识符进行早期哈希处理，采用不可逆哈希自动化系统。考虑到自动移除操作可能无法覆盖所有标识符，研究团队还对数据集进行了人工审核，以确保符合研究伦理要求并完成彻底的匿名化处理。