Next Article in Journal
A Sample of Resilient Intercultural Coexistence in Ethnic Hungarian, Serbian and Bulgarian Communities in Western Romania
Next Article in Special Issue
How Hoteliers Act in the Form of Organized Crime in Human Trafficking: A Case Study from Turkey
Previous Article in Journal
Digital Exclusion and the Structural Barriers to Safety Strategies among Men and Non-Binary Sex Workers Who Solicit Clients Online
Previous Article in Special Issue
August Vollmer, Traffic in Women, and the Theory of Organized Crime
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Brief Report

Policing Sex Trafficking in the ‘Virtual Red-Light District’: A Research Note

by
Xavier L’Hoiry
1,
Alessandro Moretti
2 and
Georgios A. Antonopoulos
3,*
1
Department of Sociological Studies, University of Sheffield, Sheffield S10 2TU, UK
2
Department of Anthropology, University of Copenhagen, 13153 Copenhagen, Denmark
3
Department of Social Sciences, Northumbria University, Newcastle NE1 8ST, UK
*
Author to whom correspondence should be addressed.
Soc. Sci. 2022, 11(8), 319; https://doi.org/10.3390/socsci11080319
Submission received: 7 July 2022 / Revised: 18 July 2022 / Accepted: 19 July 2022 / Published: 22 July 2022
(This article belongs to the Collection Tackling Organized Crime and Human Trafficking)

Abstract

:
Working alongside a police force in the United Kingdom, the study briefly presented in this note, sought to create an analytical tool (the Sexual Trafficking Identification Matrix—STIM) with which policing actors could distinguish between Adult Services Website (ASW) profiles posted by independent sex workers and profiles created by traffickers. Distinguishing between these will potentially allow law enforcement agencies to prioritise their investigatory efforts more efficiently.

Advancements in information and communication technology in the past two decades have presented organised crime actors with new opportunities for the exploitation of victims and illegal profiteering. This is evident in the context of human trafficking for the purposes of sexual exploitation, and one such example comes in the use of Adult Service Websites (ASWs) by traffickers (see Antonopoulos et al. 2020). ASWs are online platforms on which sex workers post profiles advertising their services, effectively creating a “virtual red-light district” (Cauduro et al. 2009, p. 59) connecting sex workers and their clients online. In recent years, however, traffickers have made increased use of ASWs, using this platform to post profiles advertising their victims, falsely portraying them as consenting sex workers. Distinguishing between profiles posted by independent sex workers and those posted by traffickers presents a key challenge for law enforcement agencies. Working alongside South Yorkshire Police, the study that we briefly present in this note, sought to create an analytical tool (the Sexual Trafficking Identification Matrix—STIM) with which policing actors could distinguish between ASW profiles posted by independent sex workers and profiles created by traffickers. Distinguishing between these will potentially allow law enforcement agencies to prioritise their investigatory efforts more efficiently1.
The project comprises four key phases. Firstly, a literature review of existing work concerning the use of ASWs by human traffickers was conducted. This review collated the findings of previous research on the indicators of suspect ASW profiles. Secondly, 27 interviews were conducted with a range of experts in human trafficking, sexual exploitation and the use of ASWs. Interviewees included law enforcement officers and analysts, legal representatives, NGO representatives and academic researchers. The interviews acted as a consensus building exercise, contributing to the creation of the STIM alongside the findings of the literature review. Thirdly, the STIM was used by South Yorkshire Police officers and analysts as part of a live operation to analyse ASW profiles and identify profiles highly indicative of trafficking activity. Finally, South Yorkshire Police officers took part in a focus group to provide feedback to the project team on the STIM, its operational utility as well as its limitations in practice. Based on this feedback, a second iteration of the STIM was created and delivered to South Yorkshire Police.
Interviews with practitioners and other experts in this field yielded a broad consensus that examining ASW profiles can offer a crucial entry point for the investigation of human trafficking and sexual exploitation. Although ASWs undoubtedly facilitate traffickers’ activities, the use of any online platform by an offender inevitably results in a digital fingerprint which law enforcement agencies can investigate. Moreover, data potentially available from ASWs may also provide a wealth of evidence to aid in the prosecution of traffickers.
Interview participants were asked, based on their expert knowledge and professional experience, to suggest the types of indicators one may expect to find on an ASW profile posted by a trafficker, as opposed to one posted by an independent sex worker. Many of their suggestions echoed the indicators identified in previous research (e.g., Ibanez and Suthers 2014; Ibanez and Gazan 2016a, 2016b; Diba et al. 2017). Key indicators identified by participants included:
  • Particularly explicit photographs (e.g., more explicit than other ASW profiles);
  • Use of third person language in the advert (e.g., ‘she’/‘they’);
  • Poor use of language with spelling mistakes and broken English;
  • A low price for sexual services, relative to the local marketplace;
  • A wide range of sexual services offered with seemingly no limits;
  • Being advertised as ‘in-calls only’—suggesting lack of independence/autonomy and control of movement;
  • References to spas and massage parlours;
  • Indicators of recent arrival/movement e.g., ‘new in town’/‘just arrived’.
These and other potential indicators were synthesized into the Sexual Trafficking Identification Matrix (STIM), a tool designed to enable users to analyse any given ASW profile and determine how many of the indicators are evident in the profile. Having applied the STIM to a series of ASW profiles in a live operation, officers and analysts at South Yorkshire Police offered a number of reflections:
  • The STIM proved to be a user-friendly tool which enabled a relatively rapid sifting of low-, medium- and high-risk ASW profiles. This allowed officers and analysts to prioritise their resources more effectively towards higher risk profiles and ensured some degree of consistency and rigour in their initial examination of ASW profiles.
  • A key benefit of the STIM is its ability to align to the local marketplace for sex work and human trafficking for the purposes of sexual exploitation. Different geographical areas tend to show variances in some aspects of the local sex work marketplace, including differences around pricing of sexual services, the use of massage parlours or the ethnic backgrounds of trafficked women. The STIM can be rapidly altered by users to mould around these local variances, meaning that it could potentially be adapted by other forces in different areas.
  • The danger of false positives remains. In one instance, the STIM identified an ASW profile as highly indicative of trafficking but further investigation revealed the profile to be used by an independent sex worker. The indicators flagged by the STIM in this instance were false positives. This is a useful reminder of the limitations of analytical tools such as the STIM, and it reinforces the importance of using such tools within a broader suite of other risk assessment measures.
  • Although analytical tools such as the STIM can complement investigatory efforts, police officers’ experience and knowledge remain a key component of these investigations. Knowledge of the local marketplace, intelligence on known offenders and existing contacts with sex workers were all deployed alongside the use of the STIM by officers and analysts during the study. This key occupational expertise and experience was critical in mitigating the limitations of the STIM and maximising its potential benefits.
This study revealed the positive contribution an analytical tool such as the STIM can make to existing practices in tackling trafficking and sexual exploitation. As traffickers make greater use of platforms such as ASWs to exploit their victims, so too can law enforcement agencies use the same platforms to track and apprehend offenders. Alongside police officer expertise and experience, tools such as the STIM can help to more effectively identify high-risk ASWs profiles, ensuring that police resources are more effectively targeted and deployed. The study we briefly present in this research note was an exploratory one and there is, of course, much scope for improvement. One of the changes we will adopt is integrating sex workers’ collectives in the research design. This will be critical to mitigate against the risk of ‘false positives’ being produced by the STIM. Moreover, engaging with sex workers’ collectives will allow for a broader discussion of the policing of commercial sexual exploitation, including how to mitigate the known risks of unnecessary police intervention with non-trafficked sex workers. In addition, future research will involve multiple police forces using the STIM, in order to secure (a) a wider geographical span across the UK as well as areas in which there is known sexual exploitation activity, and (b) a larger volume of sex trafficking cases online to allow us to make meaningful observations about the phenomenon and its policing.

Funding

The study this research note is based on was funded by the N8 Policing Research Partnership. Alessandro Moretti was also financially supported by the European Union’s Horizon 2020 Research and Innovation Programme [Grant agreement #725194].

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgments

We would like to thank the guest editor of the special issue, James O. Finckenauer for the invitation to contribute this brief note, as well as the reviewers for their comments and suggestions on an earlier draft.

Conflicts of Interest

The authors declare no conflict of interest.

Note

1
A detailed account of the research has been published as (L’Hoiry et al. 2021).

References

  1. Antonopoulos, Georgios A., Gabriele Baratto, Andrea Di Nicola, Parisa Diba, Elisa Martini, Georgios Papanicolaou, and Fiamma Terenghi. 2020. Technology in Human Smuggling and Trafficking. Cham: Springer. [Google Scholar]
  2. Cauduro, Andrea, Andrea Di Nicola, Chiara Fonio, Andrea Nuvoloni, and Paolo Ruspini. 2009. Innocent when you dream: Clients and trafficked women in Italy. In Prostitution and Human Trafficking: Focus on Clients. Edited by Andrea Di Nicola, Andrea Cauduro, Marco Lombardi and Paolo Ruspini. New York: Springer, pp. 31–66. [Google Scholar]
  3. Diba, Parisa, Georgios Antonopoulos, and Georgios Papanicolaou. 2017. Improving and Sharing Knowledge on the Internet’s Role in the Human Smuggling and Trafficking Process: UK Report. Report to the European Commission. Available online: https://www.semanticscholar.org/paper/Improving-and-sharing-knowledge-on-the-Internet%E2%80%99s-Diba-Antonopoulos/4c22f96f1c97b18333081fa484c6fee5c3adb6d9 (accessed on 7 July 2022).
  4. Ibanez, Michelle, and Daniel D. Suthers. 2014. Detection of domestic human trafficking indicators and movement trends using content available on open internet sources. Paper presented at 2014 47th Hawaii International Conference on System Sciences, Waikoloa, HI, USA, January 6–9; pp. 1556–65. [Google Scholar]
  5. Ibanez, Michelle, and Rich Gazan. 2016a. Detecting sex trafficking circuits in the US through analysis of online escort advertisements. Paper presented at 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), San Francisco, CA, USA, August 18–21; pp. 892–95. [Google Scholar]
  6. Ibanez, Michelle, and Rich Gazan. 2016b. Virtual indicators of sex trafficking to identify potential victims in online advertisements. Paper presented at 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), San Francisco, CA, USA, August 18–21; pp. 818–24. [Google Scholar]
  7. L’Hoiry, Xavier, Alessandro Moretti, and Georgios A. Antonopoulos. 2021. Identifying sex trafficking in Adult Services Websites: An exploratory study with a British police force. Trends in Organized Crime, 1–22. [Google Scholar] [CrossRef]
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

L’Hoiry, X.; Moretti, A.; Antonopoulos, G.A. Policing Sex Trafficking in the ‘Virtual Red-Light District’: A Research Note. Soc. Sci. 2022, 11, 319. https://doi.org/10.3390/socsci11080319

AMA Style

L’Hoiry X, Moretti A, Antonopoulos GA. Policing Sex Trafficking in the ‘Virtual Red-Light District’: A Research Note. Social Sciences. 2022; 11(8):319. https://doi.org/10.3390/socsci11080319

Chicago/Turabian Style

L’Hoiry, Xavier, Alessandro Moretti, and Georgios A. Antonopoulos. 2022. "Policing Sex Trafficking in the ‘Virtual Red-Light District’: A Research Note" Social Sciences 11, no. 8: 319. https://doi.org/10.3390/socsci11080319

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop