Social Network Analysis and Artificial Intelligence: Methodological Partners in the Study of HIV Prevention and Risk Online

Dr. Lindsay Young
When: March 6, 2019 @ 4:00pm - 5:00pm
Location: ZHS (Zumberge Hall) 252
Audiences: All are welcome to attend
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This lecture satisfies requirements for CSCI 591: Research Colloquium.

ABSTRACT

As transmitters of information and progenitors of behavioral norms, social networks are critical mechanisms of HIV prevention and risk in impacted populations like men who have sex with men (MSM), people who inject drugs (PWID), and homeless youth. Today, widespread use of online social networking technologies (e.g., Facebook, Instagram, Twitter) yield unprecedented amounts of relational and communication data far richer than anything previously collected in offline (physical) network settings. However, parsing these complex data into tractable insights and solutions requires an innovative and flexible computational toolkit that extends beyond traditional approaches. In this talk, Dr. Young will discuss her ongoing efforts to unpack how HIV prevention and risk manifest in the Facebook networks of young MSM using a hybrid of computational methods that include social and semantic network analysis and machine learning approaches for textual analysis and predictive modeling.  She will conclude with a discussion of the practical implications of this work and outstanding challenges that require further exploration.

BIO

Dr. Lindsay Young is a NIH Pathway to Independence Award Postdoctoral Fellow at the University of Chicago Department of Medicine and Chicago Center for HIV Elimination (CCHE).  Trained as a social scientist and network methodologist, she now applies those perspectives to understand the social and communicative contexts of HIV risk and prevention among young sexual minorities and other vulnerable populations. She is particularly interested in how online social network data can be leveraged for behavioral research and interventions.

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