IDTraffickers：一个用于在陪侍广告文本中关联和连接潜在人口贩运活动的作者归属数据集
IDTraffickers: An Authorship Attribution Dataset to link and connect Potential Human-Trafficking Operations on Text Escort Advertisements
AI总结：
本研究发布了包含8万余条陪侍广告文本的IDTraffickers数据集，通过训练DeCLUTR-small模型建立作者归属基准，助力执法机构识别关联潜在人口贩运活动。
摘要：
人口贩运（HT）是一个普遍存在的全球性问题，影响着弱势群体，侵犯了他们的基本人权。调查显示，大量人口贩运案件与网络广告相关，尤其是陪侍市场的广告。因此，识别和关联人口贩运贩子对执法机构（LEAs）来说变得越来越具挑战性。为解决这一问题，我们推出了IDTraffickers，这是一个包含87595条文本广告和5244个贩子标签的大规模数据集，用于验证和识别网络陪侍市场中的潜在人口贩运贩子。为建立作者识别基准，我们训练了一个DeCLUTR-small模型，在闭集分类场景下取得了0.8656的宏F1分数。随后，我们利用从训练好的分类器中提取的风格表征进行作者验证，在开集排序场景下取得了0.8852的平均r精度分数。最后，为推动进一步研究并确保负责任的数据共享，考虑到数据的敏感性，我们计划在特定条件下向研究人员开放IDTraffickers用于作者归属任务。我们相信，该数据集和基准的可用性将助力未来研究人员利用我们的研究成果，从而有效关联陪侍广告，并开发更稳健的人口贩运指标识别方法。
英文摘要：
Human trafficking (HT) is a pervasive global issue affecting vulnerable individuals, violating their fundamental human rights. Investigations reveal that a significant number of HT cases are associated with online advertisements (ads), particularly in escort markets. Consequently, identifying and connecting HT vendors has become increasingly challenging for Law Enforcement Agencies (LEAs). To address this issue, we introduce IDTraffickers, an extensive dataset consisting of 87,595 text ads and 5,244 vendor labels to enable the verification and identification of potential HT vendors on online escort markets. To establish a benchmark for authorship identification, we train a DeCLUTR-small model, achieving a macro-F1 score of 0.8656 in a closed-set classification environment. Next, we leverage the style representations extracted from the trained classifier to conduct authorship verification, resulting in a mean r-precision score of 0.8852 in an open-set ranking environment. Finally, to encourage further research and ensure responsible data sharing, we plan to release IDTraffickers for the authorship attribution task to researchers under specific conditions, considering the sensitive nature of the data. We believe that the availability of our dataset and benchmarks will empower future researchers to utilize our findings, thereby facilitating the effective linkage of escort ads and the development of more robust approaches for identifying HT indicators.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
