Abstract
Marijuana has been legalized for medical and recreational use in many states across the U.S. Despite some medical benefits, over the past decade, researchers around the globe have documented the health risks associated with marijuana use in both youths and adults. Monitoring and understanding the related concerns and activities of marijuana use play key roles in preparing and making appropriate policies for public health regulations. However, accurately and efficiently obtaining such information is very challenging due to the unique characteristics of the relevant users, where related activities are usually hidden or undercovered. In this book chapter, we discuss new approaches to reveal the related information of marijuana use in the community by exploiting information exchanged or posted in social networks. We show that data mining approaches can be used to shed some light on the hidden patterns and related activities of marijuana use from information collected in social networks (e.g., Craigslist and Twitter). Our approaches can be utilized as a new way for public health regulators to efficiently monitor and surveil-related activities of marijuana use.
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Nguyen, A., Pham, H., Nguyen, D., Tran, T. (2017). Towards Monitoring Marijuana Activities via User-Generated Content Platforms and Social Networks. In: Shaban-Nejad, A., Brownstein, J., Buckeridge, D. (eds) Public Health Intelligence and the Internet. Lecture Notes in Social Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-68604-2_7
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DOI: https://doi.org/10.1007/978-3-319-68604-2_7
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