Using Knowledge Management to Assist in Identifying Human Sex Trafficking

Hultgren, Marisa; Jennex, Murray E.; Persano, John; Ornatowski, Cezar M.

doi:10.1109/hicss.2016.539

Cited by 11 publications

(10 citation statements)

References 8 publications

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“…This is the most novel aspect of this work, since (despite all the illicit activity happening online) surprisingly little can be said with certainty about the online sex domain or the disturbing growth of its impact. By some estimates, human trafficking alone is a multi-billion dollar industry globally; unfortunately, due to socio-technical causes, it was not well-studied using computational science methods till quite recently (Hultgren et al 2016;Alvari et al 2016). Systems that can assists NGOs and law enforcement exist, of course; for example, in our group, we built the DIG (Domain-specific Insight Graphs) system (Szekely et al 2015) to help law enforcement selectively ferret out ads that are indicative of human trafficking.…”

Section: Online Sex Markets and Artificial Intelligencementioning

confidence: 99%

“…In this article, we focus on the sex marketplace, where sex providers advertise their services online for potential customers to find and solicit (Edelman and Stemler 2019). Unlike many online transactions of an illicit nature, such as drugs or even weapons, the online sex marketplace is an interesting one because it has an outsize presence both on the Dark Web and the normal Web (Hultgren et al 2016;Alvari et al 2016). On the normal Web, such advertisements can (and to a great extent, are) accessed by non-technical users on a normal website such as a classified-ads portal like backpage.com.…”

Section: Introductionmentioning

confidence: 99%

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Network-theoretic modeling of complex activity using UK online sex advertisements

Kejriwal

2020

Appl Netw Sci

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Online sex has become a fast-growing business in both developing and developed network, with advertisements of (not necessarily unique) individuals numbering in the hundreds of millions across different Web portals. One such major hub of sex advertisement activity, before it was shut down by US federal agencies, was backpage.com. The backpage.com website was a classifieds-advertising portal that had become the largest marketplace for buying and selling sex by the time that federal law enforcement agencies seized it in April 2018. Since then, investigations have been actively underway. However, the data (which has recently been made available to us for research on UK Backpage) also offers valuable insights into the nature of the online sex business, including complex properties that can be best studied using network science. One of the challenges, however, is a rigorous modeling of the data as a network, since the primary data are web advertisements and metadata (backend database) on accounts that posted that ad. In this article, we conduct an empirical study of an important sample of the online sex marketplace using UK backpage, including presenting a methodology for constructing simple 'activity networks' that define some notion of real-world collaboration or connection between two entities (in our case, at the level of ad-posting accounts) and then studying the properties of these networks. We gather a set of insights into a domain that has not been studied at scale, let alone a national level, but that is continuing to be a growing social problem for many countries.

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Section: Online Sex Markets and Artificial Intelligencementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Network-theoretic modeling of complex activity using UK online sex advertisements

Kejriwal

2020

Appl Netw Sci

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“…One of the most important aspects that separate this work from prior work is its focus on a non-traditional domain such as human trafficking (HT) that has an outsize presence on the Web. By some estimates, HT is a multi-billion dollar industry; however, due to both technical and social reasons, it has largely been ignored by the computational sciences till quite recently (Alvari et al 2016;Hultgren et al 2016). A notable exception in the knowledge graph construction domain is the DIG (Domain-specific Insight Graphs) system (Szekely et al 2015).…”

Section: Human Trafficking (Ht)mentioning

confidence: 99%

“…We do not claim causation in any form, however, only that the network metrics are predictive of accuracy metrics by virtue of the correlation. More formal models that go into depth into such theoretical issues were presented in (Hultgren et al 2016(Hultgren et al , 2018Whitney et al 2018).…”

Section: Human Trafficking (Ht)mentioning

confidence: 99%

Network-theoretic information extraction quality assessment in the human trafficking domain

Kejriwal

Kapoor

2019

Appl Netw Sci

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Information extraction (IE) is an important problem in Natural Language Processing (NLP) and Web Mining communities. Recently, IE has been applied to online sex advertisements with the goal of powering search and analytics systems that can help law enforcement investigate human trafficking (HT). Extracting key attributes such as names, phone numbers and addresses from online sex ads is extremely challenging, since such webpages contain boilerplate, obfuscation, and extraneous text in unusual language models. Assessing the quality of an IE system is an important problem that is particularly problematic in this domain due to lack of gold standard datasets. Furthermore, building a robust ground truth from scratch is an expensive and time-consuming task for social scientists and law enforcement to undertake. In this article, we undertake the empirical challenge of analyzing the quality of IE outputs in the HT domain without the provision of laboriously annotated ground truths. Specifically, we use concepts from network science to construct and study an extraction graph from IE outputs collected over a corpus of online sex ads. Our studies show that network metrics, which require no labeled ground truths, share interesting and consistent correlations with IE accuracy metrics (e.g., precision and recall) that do require ground-truths. Our methods can potentially be applied for comparing the quality of different IE systems in the HT domain without access to ground-truths.

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“…To counter these limitations researchers have investigated technology focused approaches to identify victims of human trafficking using data sources other than self-reporting. One approach is to analyze online and mobile communications and ads using text analysis techniques such as ontologies of keywords and phone number distribution that represent a victim to search online ads (Hultgren, et al, 2016). However, the volume of unstructured data and high speed of new data creation makes it difficult for law enforcement to monitor online criminal activities so researchers are also looking at ways to automate searching.…”

Section: Introductionmentioning

confidence: 99%

The Use of EMOJIS in Online Human Sex Trafficking Ads

Whitney,

Elkins,

Jennex

et al. 2023

JKMP

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Technology has dramatically changed the way criminals conduct their illicit activities. Specifically, the Internet has become a major facilitator of online human sex trafficking. Traffickers are using these technologies to market their victims which presents new challenges for efforts to combat sex trafficking. This study used knowledge management principles and natural language processing methods to develop an improved ontology of online sex trafficking ads. The language of these ads is constantly evolving; therefore, this study explored the role of a new type of indicator, emojis, to the ontology of human trafficking indicators.

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Using Knowledge Management to Assist in Identifying Human Sex Trafficking

Cited by 11 publications

References 8 publications

Network-theoretic modeling of complex activity using UK online sex advertisements

Network-theoretic modeling of complex activity using UK online sex advertisements

Network-theoretic information extraction quality assessment in the human trafficking domain

The Use of EMOJIS in Online Human Sex Trafficking Ads

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