Covert Online Ethnography and Machine Learning for Detecting Individuals at Risk of Being Drawn into Online Sex Work

@article{Kostakos2018CovertOE,
  title={Covert Online Ethnography and Machine Learning for Detecting Individuals at Risk of Being Drawn into Online Sex Work},
  author={Panos Kostakos and Lucie Sprachalova and Abhinay Pandya and Mohamed Aboeleinen and Mourad Chabane Oussalah},
  journal={2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)},
  year={2018},
  pages={1096-1099}
}
How can we identify individuals at risk of being drawn into online sex work. [] Key Method Unlike prior work which focuses exclusively on either qualitative or quantitative methods, in this paper we combine covert online ethnography with semi-supervised learning methodologies, using data from a popular European adult forum. We obtained risk assessment results of 78 users using covert online ethnography, and set out to build a machine learning model that can predict the risk factor in other 28,832 users…

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