The ICSR social media team is focused on understanding how ordinary users on various platforms might be served harmful, extreme, or conspiratorial content, and the roles played by the platforms' algorithms in facilitating that exposure.
"We're particularly interested in how a representative user who joins a platform like Twitter to engage with a mundane topic might be funneled toward seeing content and following users who promote more harmful or controversial views," says IDSS researcher and Hammer Fellow Zach Schutzman. "For example, how might a young person interested in feminism be pushed toward racist, xenophobic, or transphobic parts of the network?"
Answering this question and many others involves several different avenues of work including computational infrastructure and machine learning tools to collect and analyze enormous amounts of data, as well as qualitative analysis of the kinds of interests users in various communities have and the ways those users engage with the platform.
The social media team includes SES students Erin Walk and Chris Hays (pictured above), with contributions from UROP students. The undergraduate UROP students are also involved at all levels, from using machine learning tools to process and interpret social media content to figuring out how to access and collect the data that underpins those models. "These students' insight and input has been valuable in steering the project and understanding which topics and questions to analyze and investigate," says Zach.
