University of Pittsburgh

What do you think of vaping? Machine learning methods for Twitter stance detection

graduate student
Date: 
Friday, November 8, 2019 - 12:30pm - 1:00pm

Abstract: Electronic nicotine delivery systems (ENDS), commonly known as e-cigarettes or vape devices, are widely used for smoking cessation. However, as evidenced in current news media, vaping may pose serious health hazards. The popularity of vape devices, particularly Juul, among young adults has given rise to a vaping epidemic, calling for a need to measure and understand the risks, behaviors and outcomes related to vaping. The social media platform Twitter has a large user base and has been successfully used in the past for tracking health conditions and outbreaks. This talk presents the work done by the presenter as a Research Assistant at the Center for Research on Media, Technology and Health (CRMTH) at the School of Medicine. We compare machine learning methods for classification of Twitter messages based on relevance to vaping, promotional content and user stance toward vaping. Our goal is to use Twitter as a surveillance system to identify changes in content over time as well as assess unique user perspectives related to e-cigarettes.

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