Department of Media and Information faculty member and AT&T Scholar Emilee Rader, won a $486,000 grant with the National Science Foundation (NSF) to study the effects of automated information selection. This is her second currently active NSF grant.
Automated information selection methods, also known as algorithmic content curation, are sets of automated rules that control the content people can see and interact with online. These methods allow the display of some pieces of information while hiding others based on user-specific data collected by companies as people interact with their online systems. This technology is often used in Internet search engines, social media platforms such as Facebook and news aggregators, among others.
"What we see online is increasingly decided by algorithms. These algorithms are designed by people, but sometimes behave in ways that can be hard to predict," Rader said. "My goal is to be able to explain some of the complex dynamics involved when a system depends on both people and technology, and provide guidance for designers of algorithms for how to make systems that behave in predictable ways."
Rader's work will investigate the effects of how algorithmic content curation processes influence what users see and interact with online as influenced by their behavior and decision-making while using web-based tools. Over the course of the research, Rader will use targeted lab experiments, field studies and agent-based modeling to study this process as well as its effect on societal norms and decisions.
This material is based upon work supported by the National Science Foundation under Grant No. IIS-1217212 (). Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).Share via these networks: