University of Maryland

Seed Grant

May 7 – SoDa Seed Grant Series: Do County Demographics Shape Exposure to Cyber Harm? Exploring Socio-Economic Factors Influencing Integrated Attack Surface Size and Vulnerability

Date: May 7, 2024 Time: 12:00pm – 1:00pm Location: Zoom WATCH VIDEO! Project Title: Correlating Population Demographics with Maryland’s County-Level Critical Infrastructure Vulnerabilities Abstract: Local government-controlled critical infrastructure relies on computer systems and is increasingly vulnerable to cyber-attacks that can disrupt its operation impacting citizens’ daily lives. While some research has looked at user characteristics […]

April 25 – SoDa Seed Grant Series: How Can Large Language Models Help Us Identify and Use Constructs that We Can Trust?

Date: Thursday, April 25, 2024 Time: 12:00pm – 1:00pm Location: Zoom WATCH VIDEO Abstract: The idea of a construct is central in the psychological and social sciences: constructs are abstract categories like empathy, misinformation, or benefits of social interaction that are operationalized in order to make them measurable. Social scientists spend an enormous amount of […]

SoDa Seed Grant Series: Newspapers and the Lynching Story: Discoveries, Distortions, and Erasure, 1789-1963

Date: Tuesday, December 12, 2023Time: 12:00pm – 1:00pmLocation: Zoom   Abstract: Our project examines media coverage of lynching from 1789 to the current era. Researchers examined metadata of 60,000 pages of news coverage in the Library of Congress’ Chronicling America database and conducted a computational text analysis of a stratified sample. We find that some […]

SoDa Seed Grant Series: Socio-Algorithmic Foundations of Trustworthy Recommendations

Date: February 27, 2024 Time: 12:30pm – 1:30pm Location: Zoom

SoDa Seed Grant Series: How Can Data Science Be Used For Racial Equity?

Date: TBD, Fall 2024 Time: TBD Location: Zoom Abstract: Data science methods are increasingly being applied to large-scale educational data, but there has been less attention on the possibility of algorithmic bias. In this presentation, we present several metrics used for algorithmic bias, discuss how proportions of racial groups impact the presence of algorithmic bias, […]