My research focuses on combining computational social science approaches with alternative data (e.g., demographic data from the Facebook Marketing API) and traditional data (e.g., American Community Survey, Census) to evaluate population dynamics such as migration patterns during a disaster. As a computational social scientist, my interests include structural inequality, natural language processing, and developing programming solutions (policy and software) to social problems. I'm passionate about growing the community of computational social scientists and teach in Software Carpentry and Data Carpentry Workshops.
In Autumn 2021, I was excited to be the instructor for Data and Society (SOC 225) at UW. This lab and lecture course explores how digital data is being used in contemporary society and the effects for individuals and institutions. By focusing on technologies from smartphones to social media, students in SOC 225 investigate how digital data is produced, collected, and analyzed by individuals, corporations, and governments. I am grateful to UW administrators and students for the opportunity to teach this course.
I will place open source materials used by the course here
Kivan Polimis