Researchers leverage inferences between social science and computer science fields in Community of Practice

Bear Braumoeller

By using computational techniques and big data to gain insights into basic social processes not easily identified with conventional methods, the Computational Social Sciences team hosted by TDAI works to facilitate research and collaboration between social science and computer science and develop novel problem-solving methods. This Community of Practice (CoP) is led by Bear Braumoeller, a Professor in the department of Political Science in the College of Arts and Sciences, and Sean Downey, Associate Professor of Anthropology.

When asked to describe computational social science, Braumoeller said the answers typically differ from person to person. “If you were to ask a social scientist this question, many of them think about it as social scientists who are good with computers. The goal of our CoP is to try to forge a deeper and more thorough collaboration between social scientists and computer scientists.” The advent of faster and less expensive computing power and big data has transformed the way that people study biology and genetics, but has not had as much of an impact on social sciences. Therefore it is crucial that computer scientists and social scientists combine their skills and form a fuller, more fundamental connection between the two fields to solve complex problems.

Currently, the Social Sciences CoP is working on setting up a Graduate Interdisciplinary Specialization (GIS) in Computational Social Science at Ohio State. “Our main curricular goal for the coming year is to lay the groundwork for this new specialization,” said Braumoeller. The GIS is what the graduate school calls a degree enhancement, which allows people to study and specialize in something that interests them. It must consist of coursework in at least three different departments, and be between 10 and 20 credit hours. As for the foreseeable timeline, Braumoeller hopes to start this program in May. “We are envisioning using the May-mester as a boot camp, to get everyone up to speed on fundamentals, then allowing them to specialize depending on their particular interest.” Braumoeller said at the end of the program each student will come back together for a capstone class that will apply their knowledge and skills to problems generated by either his team or their industry partners.

With regards to interdisciplinary work, Braumoeller said this aspect is huge for the success of their program. As a political scientist, Braumoeller has a certain perspective of social science but can bounce his ideas off of individuals within TDAI who are from other disciplines. “They bring in considerations I’d never really thought about. Sean is a big proponent of leveraging computational social science to help with problems related to small data. The interdisciplinary aspect is essential because it helps us get a bigger picture of what characteristics are unique to one social science and which ones are shared across them,” said Braumoeller. Equally important to their team are the connections Braumoeller said he has been able to make in computer science and the help from individuals such as Rajiv Ramnath and Tanya Berger-Wolf which have provided him with a deeper understanding of how computer scientists think about foundational things such as theories. Their biggest challenge is finding out how to incorporate the different ways that social scientists make inferences from data and the ways in which computer scientists make inferences and create a coherent whole. Braumoeller said having the extra insight across multiple disciplines and fields, “could only be done with an engaged interdisciplinary team, and TDAI is one of the best places I’ve ever found to create this type of engagement.”

When considering the future timeline of their work, Braumoeller hopes to increase engagement opportunities. In the past, his team has held monthly meetings where each member can highlight their research, and they are working to get these up and going in a virtual format in the coming months. They have recently secured speaker and author David Lazer, a political scientist at Northeastern University, to present on his innovations in the field of computational social science. Braumoeller said this COVID-19 era has shifted their main focus to consideration of ways to embark on collaborative efforts in the future.

To learn more about the COP or to join, visit the Computational Social Sciences Community of Practice page.

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