“Spotting the signs” of trafficking recruitment online: exploring the characteristics of advertisements targeted at migrant job-seekers

Abstract

Despite considerable concern about how human trafficking offenders may use the Internet to recruit their victims, arrange logistics or advertise services, the Internet-trafficking nexus remains unclear. This study explored the prevalence and correlates of a set of commonly-used indicators of labour trafficking in online job advertisements. Taking a case study approach, we focused on a major Lithuanian website aimed at people seeking work abroad. We examined a snapshot of job advertisements (n = 430), assessing both their general characteristics (e.g. industry, destination country) and the presence of trafficking indicators. The vast majority (98.4%) contained at least one indicator, suggesting certain "indicators" may in fact be commonplace characteristics of this labour market. Inferential statistical tests revealed significant but weak relationships between the advertisements' characteristics and the number and nature of indicators present. While there may be value in screening job advertisements to identify potential labour trafficking and exploitation, additional information is needed to ascertain actual labour trafficking. We conclude with an outlook on automated approaches to identifying cases of possible trafficking and a discussion of the benefits and ethical concerns of a data science-driven approach.

Identifying human trafficking indicators in the UK online sex market

“…Perhaps more importantly, one of this study's main findings concerns the elusive nature of human trafficking indicators. While Volodko et al (2020) posit that some indicators are more useful than others, we find that it is hard to conclude which of these indicators are sufficiently reliable for identifying human trafficking given the dearth of empirical research in this area. This introduces the problem of 'false positives' and 'false negatives'.…”

“…Shutting down websites advertising sex workers' services due to concern over traffickers' use of them has two potential negative consequences. First, traffickers can easily move to alternative platforms and continue to advertise trafficked sex workers (Heil & Nichols, 2014;Volodko et al, 2020). Second, it can further marginalise legitimate sex workers who lose out on the benefits of these platforms, and push them into more risky settings.…”

“…As some studies underscore (e.g. Volodko et al 2020;Bounds et al 2020;Dubrawski et al 2015), at best, such research can simply flag up suspicious advertisements that deserve closer attention from law enforcement and practitioners. What it cannot do is identify cases of human trafficking.…”

Good Tech, Bad Tech: Policing Sex Trafficking with Big Data

“…In other words, the social dimension of sex trafficking must be operationalised before we can elucidate any trends or patterns within the data (Kaufmann, Egbert and Leese 2019). This has proven to be a challenging task, especially for machine learning approaches in which the indicators used for labelling training data are problematic and could equally apply to individuals and groups that are not subjected to exploitation (Volodko et al 2019). These are issues of measurement validity; it is difficult to operationalise a concept for statistical analysis without any substantive knowledge about the market prerogatives used by criminal networks.…”

Narratives of human trafficking: Defining policy, practice and positioning in a contested field

“…The nature of many trafficking cases discussed within the reports and interviews suggests that trafficking often takes place within communities, between people who have some kind of family or community tie, or within employment and business arrangements. This singling out of 'trafficked people' through victim spotting is also problematic as research from Volodko, Cockbain and Kleinberg suggests that it is difficult to find reliable indicators that can be used to 'spot' victims (Volodko et al, 2020). In particular, indicators that have been used by commercial companies or law enforcement do not differentiate between sex work and trafficking and there is a risk that their use will result in the indiscriminate targeting of sex workers who have not been trafficked (Shand-Baptiste, 2020).…”