The role of artificial intelligence and predictive analytics in social audio and broader behavioral research

Abstract

Social media data are increasingly being studied for their potential use in addressing and mitigating public health issues. Data from text and image-based social media have been used for observational and intervention studies, and have been collected from a variety of social media platforms. Artificial intelligence techniques have been used to analyze social media data for surveillance and prediction of public health concerns, including near real-time case identification of emerging infectious disease and mental health cases. A new and emerging type of social media, social audio, uses voice to engage users in conversation. This paper explores the potential use of artificial intelligence to analyze data from social audio for prediction and broader behavioral health research. Advantages of social audio over traditional social media and challenges in implementation are also discussed.