Don’t Want to Get Caught? Don’t Say It: The Use of EMOJIS in Online Human Sex Trafficking Ads

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dc.contributor.author Whitney, Jessica
dc.contributor.author Jennex, Murray
dc.contributor.author Elkins, Aaron
dc.contributor.author Frost, Eric
dc.date.accessioned 2017-12-28T02:02:32Z
dc.date.available 2017-12-28T02:02:32Z
dc.date.issued 2018-01-03
dc.description.abstract 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, emoticons, to the ontology of human trafficking indicators.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2018.537
dc.identifier.isbn 978-0-9981331-1-9
dc.identifier.uri http://hdl.handle.net/10125/50426
dc.language.iso eng
dc.relation.ispartof Proceedings of the 51st Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Knowledge Management and Information Security
dc.subject human trafficking knowledge management machine learning ontology
dc.title Don’t Want to Get Caught? Don’t Say It: The Use of EMOJIS in Online Human Sex Trafficking Ads
dc.type Conference Paper
dc.type.dcmi Text
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