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This is a University Lecture co-sponsored with the Info Sci Colloquium and the Center for Data Science for Enterprise and Society’s Data Science Distinguished Lecture Series. A reception will be held prior to the colloquium at 3:30 p.m. in Gates 306.
Andrew Piper is Professor and William Dawson Scholar in the Department of Languages, Literatures, and Cultures at McGill University. He directs the Bachelor of Arts and Science program at McGill and is editor of the Journal of Cultural Analytics. His work focuses on using the tools of data science, machine learning, and natural language processing to study human storytelling. He is the director of .txtlab, a laboratory for cultural analytics, and author most recently of, Enumerations: Data and Literary Study (Chicago 2018) and Can We Be Wrong? The Problem of Textual Evidence in a Time of Data (Cambridge 2020).
Talk: Computational Narrative Understanding and the Human Desire to Make-Believe
Abstract: Narratives play an essential role in shaping human beliefs, fostering social change, and providing a sense of personal meaning, purpose and joy. Humans are in many ways primed for narrative. In this talk, I will share new work from my lab that leverages emerging techniques in computational narrative understanding to study human storytelling at large scale. What are the cues that signal to readers or listeners that narrative communication is happening? How do imaginary stories differ from true ones and what can this tell us about the value of fictional storytelling for everyday life? How might we imagine large-scale narrative observatories to measure public and political health and well-being? As we face growing skepticism around the purpose of humanistic study, this talk will argue that data-driven and fundamentally inter-disciplinary approaches to the study of storytelling can help restore public confidence in the humanities and initiate new pathways for research that address pressing public needs.