Graduate Seminar: Data-driven Social Informatics

Event Date: 
Fri, 2017-02-10 10:00 - 11:30

Location: Rm 118, Biocomplexity Institute

Speaker: Gita Sukthankar,  University of Central Florida

Abstract:
Data-driven social informatics unites models derived from
social science with data-driven approaches in order to model and predict
population behavior patterns.  It can be used to advance our
understanding of human behavior, guide public policy decisions, and
improve user experience with social media platforms.  In this talk, I'll
describe work done at UCF's Intelligent Agents Lab
(http://ial.eecs.ucf.edu/) in which we use a combination of agent-based
modeling, machine learning, and crowdsourcing to model human social
systems.  The benefits of this approach will be illustrated using three
case studies: 1) predicting the influence of social norms on smoking
cessation behavior, 2) tracking campus parking usage using crowdsourcing
and transportation modeling, 3) learning collaboration patterns from
co-authorship networks.  We believe that the combination of techniques
yields a more nuanced view that relying on data alone.