10. Political Discourse and Substantive-Methodological Intersections with Justine Zhang and Arthur Spirling

In this episode, we talk with Justine Zhang and Arthur Spirling. Justine is currently a postdoctoral researcher at Stanford University and Arthur is a Professor of Politics and Data Science at New York University. We discuss their 2017 EMNLP paper, with Cristian Danescu-Niculescu-Mizil, "Asking too much? The rhetorical role of questions in political discourse." Justine and Arthur touch on how collaborations can provide real insight into other disciplines as well as their different paces and writing norms. We also discuss substantive validation for unsupervised learning methods, marinating in "fun" data, the responsibility of studying political institutions that touch all aspects of human life, and a call for administrators to incentivize these kinds of collaborations.

Om Podcasten

Large-scale data has become a major component of research about human behavior and society. But how are interdisciplinary collaborations that use large-scale social data formed and maintained? What obstacles are encountered on the journey from idea conception to publication? In this podcast, we investigate these questions by probing the “research diaries” of scholars in computational social science and adjacent fields. We unmask the research process with the hope of normalizing the challenges of and increasing accessibility in academia. Music: Jon Gillick.