Cyber Crime and Cyber Terrorism

APPLICATION OF SOCIAL MEDIA IN HUMAN TRAFFICKING 
SCENARIOS
Human Trafficking is a diverse and complex international problem. Due to its glo-
balized, cross-border and varied nature, any response to Human Trafficking must be 
similarly scoped (
Rankin and Kinsella, 2011
). Human Trafficking consists of any 
efforts to transport humans illegally across borders by force, or through the use of 
threats such as abduction, fraud, deception and coercion, with criminal organiza-
tions constantly identifying and exploiting new routes, modes of transportation and 
pretences upon which to illegally traffic human beings (UNODC, 2004). As well as 
being a global issue, Human Trafficking is also a growing one, with the UK's NCA 
(National Crime Agency) reporting a 9% year-over-year increase on the number of 
Human Trafficking-related convictions in the UK in 2012 (
UKHTC, 2013
). In order 
to improve the architectural underpinnings of Human Trafficking defense strategies, 
a co-ordinated, multi-disciplinary approach is required to combine the requirements 
to maximize the identification of criminal activity, and the reprehension of the indi-
viduals and illicit organizations responsible for it (
UNODC, 2012
).
Social Media provides a potential source of competitive advantage for LEAs over 
criminal organizations perpetrating crimes such as Human Trafficking (
Gottschalk, 
2010
), and is frequently considered to be an under-utilized repository of open-source 

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CHAPTER 15
Social media and its role for LEAs: Review and applications
intelligence that is traditionally under-valued in the minds and practices of police 
officers as a result of culturally ingrained bias that are deeply embedded within the 
culture and organizational mechanisms of modern policing (
Reiner, 2010
). Deep-
rooted resistances such as these require any new approaches to be underpinned by 
knowledge management-enabled organizational mechanisms, facilitating the inte-
gration of any new intelligence-led approaches to combatting organized crime threats 
such as Human Trafficking. In response to this requirement, social media is but one 
of the resources which can be leveraged in response to the ever diversifying threat 
of human trafficking through the use of text mining enabled information extraction, 
categorization and analysis. Although agents of trafficking themselves are unlikely 
to be detailing the nature of their activities in the text and images they post to social 
media, observers of the environment (i.e., the general public) are potentially quite 
likely to make posts in reference to behavior that is suspicious or out of the ordinary.
In a recent case of Human Trafficking in south-east England, a Hungarian traffick-
ing gang were convicted for transporting more than 50 teenage girls into the UK for 
the purposes of running an illegal prostitution ring. Incidents such as this provide a po-
tential use case to illustrate the application of social media analytics and information 
extraction in combatting the threat of Human Trafficking. During the case identified, a 
number of trafficking victims were smuggled into halls of residence at the University 
of Sussex for prostitution purposes (
Campbell, 2014
). In events such as this, it is likely 
that other residents at the halls, and local university students would have made inquisi-
tive posts to social media sites such as Twitter and Facebook in regards to the unusual 
nature of having a number of eastern European women suddenly appearing at the 
premises, and rarely being seen or heard from. Although the posts of observers may 
not have been inferring that the individuals were in fact victims of human trafficking, 
and operating within a forced prostitution ring, analytical techniques such as natural 
language processing (NLP) and named entity extraction, enabled through web crawl-
ing technologies, can be used in conjunction with a knowledgebase containing the 
specialist domain knowledge of Human Trafficking experts that could extract textual 
information from social media indicating multiple reports of unusual behavior being 
present from the same location that would then be categorized to indicate that it may 
in fact be related to potential illicit activity, such as Human Trafficking.
By filtering and fusing information sources, law enforcement analysts can begin 
to accumulate enough information to form a representation of the environment being 
observed, through the aggregation of information based upon the geo-tagged loca-
tion data that is embedded within social media content. The repository aspect of any 
proposed system would be populated with domain knowledge consisting of likely 
indicators of Human Trafficking activity, both in terms of the victims, the properties 
being used by those involved and the characteristics of the perpetrators themselves, 
all tied to linguistic rules designed to pick out slang terms, and posts from social 
media which would reference activity that coincides with that stored in the knowl-
edgebase. In the past, the police and LEAs would be reliant on the direct reporting 
of suspicious activity from observers, however in the new environment emergent as 
a result of the information age, this same information is dispersed within the social 

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