People are increasingly taking on to social media platforms, as Twitter and Facebook, to share their thoughts and opinions with their audiences. Often these updates are made in a naturalistic setting over the course of daily activities and happenings. Beyond elucidating core aspects of how we act, interact or emote, these platforms thus provide a promising mechanism to capture behavioral attributes relating to an individual¡¦s social and psychological environment, some of which may signal concerns about their mental health.
In this talk, we will examine the harnessing of social media as a tool in behavioral health. Today affective disorders constitute a serious challenge in public health: More than 9% of US population is known to suffer from depression. I will present two problems where social media behavior can help us reveal latent affective concerns. First, I will discuss the use of social media, particularly online activity, emotion and linguistic expression, in making inferences about behavioral changes in new mothers following childbirth. Second, I will present predictive models that leverage social media behavioral cues, to detect, ahead of onset, the likelihood of major depression in individuals. Broadly, such predictive forecasting can help develop unobtrusive diagnostic measures of behavioral disorders, and can hopefully enable behavioral health tracking and surveillance in large populations in a fine-grained manner. I will conclude with the potential of this line of research in informing the design of next generation low-cost, privacy-sensitive early-warning systems and interventions, that can bring people timely information and assistance.
Munmun De Choudhury is a postdoctoral researcher at Microsoft Research, Redmond. Her research interests are in computational social science. By combining data mining, human computer interaction, and social science, Munmun¡¦s research attempts to decipher human behavior, as manifested in people¡¦s online activities. She has been a recipient of the Grace Hopper Scholarship, a finalist of Facebook Fellowship, and winner of two Best Paper Honorable Mention awards from ACM SIGCHI. Earlier, Munmun was a research fellow at Rutgers University, and obtained a PhD in Computer Science from Arizona State University in 2011.