Detecting Health-Related Privacy Leaks in Social Networks Using Text Mining Tools
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- Ghazinour K., Sokolova M., Matwin S. (2013) Detecting Health-Related Privacy Leaks in Social Networks Using Text Mining Tools. In: Zaïane O.R., Zilles S. (eds) Advances in Artificial Intelligence. AI 2013. Lecture Notes in Computer Science, vol 7884. Springer, Berlin, Heidelberg
In social media, especially in social networks, users routinely share personal information. In such sharing, they might inadvertently reveal some personal health information, an essential part of their private information. In this work, we present a tool for detection of personal health information (PHI) in a social network site, MySpace. We analyze the PHI with the use of two well-known medical resources MedDRA and SNOMED. We introduce a new measure – Risk Factor of Personal Information – that assesses a possibility of a term to disclose personal health information. We synthesize a profile of a potential PHI leak in a social network, and we demonstrate that this task benefits from the emphasis on the MedDRA and SNOMED terms.
KeywordsMedical electronic dictionaries Personal health information Social networks Machine Learning
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