Past Events in Data Science
Ruha Benjamin, Ph.D.
Talk: May 4 at 6 PM
Race to the Future? Re-imagining the Default Settings of Technology & Society
From everyday apps to complex algorithms, technology has the potential to hide, speed, and deepen discrimination, while appearing neutral and even benevolent when compared to racist practices of a previous era. In this talk, Ruha Benjamin presents the concept of the “New Jim Code” to explore a range of discriminatory designs that encode inequity: by explicitly amplifying racial hierarchies, by ignoring but thereby replicating social divisions, or by aiming to fix racial bias but ultimately doing quite the opposite. This presentation takes us into the world of biased bots, altruistic algorithms, and their many entanglements, and provides conceptual tools to decode tech promises with historical and sociological insight. She will also consider how race is a tool designed to stratify and sanctify social injustice and discuss how technology is and can be used toward liberatory ends. In doing so, Ruha challenges us to question not only the technologies we are sold, but also the ones we manufacture ourselves.
Gauging Political Communication with Social Media Data: Research Frontier, Tools, and Caveats Online
Dr. Haohan Chen
Postdoctoral Fellow, Center for Social Media and Politics, New York University
Assistant Professor, Politics & Public Administration. University of Hong Kong
- April 28, 2021
- 4:15pm - 5:30pm
Social media data help political scientists and policymakers understand the behavioral patterns of political communication. Consider these questions: How do citizens in authoritarian countries face censorship and perform self-censorship? How and why does the American public have a growing dislike or distrust of people from the other party? How does the public update their beliefs about COVID-19 in response to elite pronouncement and media reports? In his talk, Dr. Chen will introduce how social media data, empowered by data science toolkits, can help gauge political communication. The talk will consist of two parts. The first part introduces Dr. Chen’s research projects on self-censorship and political polarization with social media data. The second part introduces tools to collect and analyze social media data for opinion studies, with a critical evaluation of their limitations and best practices.
Hosted by the Center for Social Sciences and the Data Science Program.