P. Kostakos, L. Špráchalová, A. Pandya, M. Aboeleinen and M. Oussalah, "Covert Online Ethnography and Machine Learning for Detecting Individuals at Risk of Being Drawn into Online Sex Work," 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Barcelona, 2018, pp. 1096-1099. doi: 10.1109/ASONAM.2018.8508276
Covert online ethnography and machine learning for detecting individuals at risk of being drawn into online sex work
|Author:||Kostakos, Panos1; Špráchalová, Lucie2; Pandya, Abhinay1;|
1Center for Ubiquitous Computing, University of Oulu, Oulu, Finland
2Department of Sociology, Charles University, Prague, Prague, Czech Republic
|Online Access:||PDF Full Text (PDF, 0.8 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe201901222703
IEEE Computer Society,
|Publish Date:|| 2019-01-22
How can we identify individuals at risk of being drawn into online sex work? The spread of online communication removes transaction costs and enables a greater number of people to be involved in illicit activities, including online sex trade. As a result, social media platforms often work as springboard for criminal careers posing a significant risk to the economy, public health and trust. Detecting deviant behaviors online is limited by the poor availability of ground-truth data and machine learning tools. 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. Results show that a combination-based approach in which all features are used yields the most accurate results.
International Conference on Advances in Social Network Analysis and Mining
|Pages:||1096 - 1099|
2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)
IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
|Type of Publication:||
A4 Article in conference proceedings
|Field of Science:||
113 Computer and information sciences
213 Electronic, automation and communications engineering, electronics
European Commission grant 770469-CUTLER and 645706-GRAGE.
|EU Grant Number:||
(770469) CUTLER - Coastal Urban developmenT through the LEnses of Resiliency
(645706) GRAGE - Grey and green in Europe: elderly living in urban areas
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