# An Entity Resolution approach to isolate instances of Human Trafficking online

arXiv: https://arxiv.org/abs/1509.06659 · HTML: https://mlsanity.com/paper/1509.06659/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Sep 2015.

## Built on by (most cited first, 4 of 4)

- [IDTraffickers: An Authorship Attribution Dataset to link and connect Potential Human-Trafficking Operations on Text Escort Advertisements](https://mlsanity.com/paper/2310.05484/) (2023)
- [Revisiting Hotels-50K and Hotel-ID](https://mlsanity.com/paper/2207.10200/) (2022)
- [MATCHED: Multimodal Authorship-Attribution To Combat Human Trafficking in Escort-Advertisement Data](https://mlsanity.com/paper/2412.13794/) (2024)
- [Narrative to Trajectory (N2T+): Extracting Routes of Life or Death from Human Trafficking Text Corpora](https://mlsanity.com/paper/2405.06129/) (2024)

## Abstract (arXiv)

Human trafficking is a challenging law enforcement problem, and a large amount of such activity manifests itself on various online forums. Given the large, heterogeneous and noisy structure of this data, building models to predict instances of trafficking is an even more convolved a task. In this paper we propose and entity resolution pipeline using a notion of proxy labels, in order to extract clusters from this data with prior history of human trafficking activity. We apply this pipeline to 5M records from backpage.com and report on the performance of this approach, challenges in terms of scalability, and some significant domain specific characteristics of our resolved entities.