0000-0001-8636-497XDr. Megan Stubbs-Richardson is an Associate Research Professor at the Social Science Research Center (SSRC) of Mississippi State University. She directs the Data Science for Social Sciences Laboratory at the SSRC. She is leading one of the laboratory’s missions to develop open-source social media-based infrastructure projects, aiming to broaden participation in social media research. Dr. Stubbs-Richardson has been a PI or Co-PI on projects funded by the National Science Foundation (NSF), the National Institute of Justice (NIJ), the Bureau of Justice Assistance (BJA), and the Department of Defense (DoD). She has been conducting social media data analyses at the SSRC since 2012. In her research, she utilizes digital data to identify crime patterns and trends, while also examining the role of digital data in crime prevention and control. She served as the principal investigator (PI) for the COPE-ID project, which initially provided nearly 15 million posts about how people coped during the pandemic on ten social media platforms. The database is now paired with the data visualization and analytics tool (DataViz), enabling users to easily draw down data samples and blend social and computational scientific research methods to examine the data.
Contribution to Project: PI, Dr. Stubbs-Richardson (Sociology Social Scientist), directs the Data Science for Social Sciences (DS3) laboratory and has worked with social media data since 2012. Dr. Stubbs-Richardson often collaborates with SBE scientists and computer scientists to integrate data science and social science methods across large volumes of social media data, examining various social problems. For this initiative, she has provided oversight of the two awards (NSF #2031246 and #2318438) while also leading the development of user guides for the COPE-ID database and data visualization tool (DataViz), as well as associated methods, including topic modeling user guides. She also led the effort to broaden research participation in social media data by sharing presentations with potential users and then evaluating the effectiveness of the COPE-ID data visualization tool.