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| Hauptverfasser: | , , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2405.13348 |
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| _version_ | 1866911884599361536 |
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| author | Rivas, Pablo Cerny, Tomas Perez, Alejandro Rodriguez Turek, Javier Giddens, Laurie Bichler, Gisela Petter, Stacie |
| author_facet | Rivas, Pablo Cerny, Tomas Perez, Alejandro Rodriguez Turek, Javier Giddens, Laurie Bichler, Gisela Petter, Stacie |
| contents | Our study addresses the challenges of building datasets to understand the risks associated with organized activities and human trafficking through commercial sex advertisements. These challenges include data scarcity, rapid obsolescence, and privacy concerns. Traditional approaches, which are not automated and are difficult to reproduce, fall short in addressing these issues. We have developed a reproducible and automated methodology to analyze five million advertisements. In the process, we identified further challenges in dataset creation within this sensitive domain. This paper presents a streamlined methodology to assist researchers in constructing effective datasets for combating organized crime, allowing them to focus on advancing detection technologies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_13348 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | On the Challenges of Creating Datasets for Analyzing Commercial Sex Advertisements to Assess Human Trafficking Risk and Organized Activity Rivas, Pablo Cerny, Tomas Perez, Alejandro Rodriguez Turek, Javier Giddens, Laurie Bichler, Gisela Petter, Stacie Machine Learning I.2.7 Our study addresses the challenges of building datasets to understand the risks associated with organized activities and human trafficking through commercial sex advertisements. These challenges include data scarcity, rapid obsolescence, and privacy concerns. Traditional approaches, which are not automated and are difficult to reproduce, fall short in addressing these issues. We have developed a reproducible and automated methodology to analyze five million advertisements. In the process, we identified further challenges in dataset creation within this sensitive domain. This paper presents a streamlined methodology to assist researchers in constructing effective datasets for combating organized crime, allowing them to focus on advancing detection technologies. |
| title | On the Challenges of Creating Datasets for Analyzing Commercial Sex Advertisements to Assess Human Trafficking Risk and Organized Activity |
| topic | Machine Learning I.2.7 |
| url | https://arxiv.org/abs/2405.13348 |