Automatic User Profiling in Darknet Markets: a Scalability Study

• URL: http://arxiv.org/abs/2203.13179v1
• Date: Thu, 24 Mar 2022 16:54:59 GMT
• Title: Automatic User Profiling in Darknet Markets: a Scalability Study
• Authors: Claudia Peersman, Matthew Edwards, Emma Williams, Awais Rashid
• Abstract summary: This study aims to understand the reliability and limitations of current computational stylometry approaches. Because no ground truth is available and no validated criminal data from historic investigations is available for validation purposes, we have collected new data from clearweb forums.
• Score: 15.83443291553249
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this study, we investigate the scalability of state-of-the-art user profiling technologies across different online domains. More specifically, this work aims to understand the reliability and limitations of current computational stylometry approaches when these are applied to underground fora in which user populations potentially differ from other online platforms (predominantly male, younger age and greater computer use) and cyber offenders who attempt to hide their identity. Because no ground truth is available and no validated criminal data from historic investigations is available for validation purposes, we have collected new data from clearweb forums that do include user demographics and could be more closely related to underground fora in terms of user population (e.g., tech communities) than commonly used social media benchmark datasets showing a more balanced user population.

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