I’m looking forward to the Digital Humanities conference at the University of Nebraska-Lincoln (July 16-19, 2013), where I’ll present an overview of my recent work in agent-based modeling and discuss some of its implications. The title is “Agent-Based Modeling and Historical Simulation.” Here’s a selection from the abstract:
This paper will discuss Agent-Based Modeling (ABM) and its application in the humanities, with special focus on questions of concern to literary history. I begin with an introduction to ABM. Unlike text mining, topic modeling, and social-network analysis, which apply quantitative analysis to already existing text corpora, ABM creates a simulated environment and measures the interactions of individual agents within that environment. Like video games, agent-based models simulate rule-bound behaviors and generate outcomes based on those rules. However, unlike most games, where the “procedural rhetoric” of the game “persuades” users (Bogost), ABM does not depend on human interaction, but can be run many times with changing variables. Researchers can alter the parameters of agent behavior and compare how different models generate different outcomes. In the fields of ecology, economics, and political science, ABM has been used to show how the behaviors of individual entities—microbes, consumers, and voters— collectively alter large emergent phenomena. ABM offers a promising new way to approach long- standing humanistic questions, such as how literary genres change over time, how publics form and transform, how consumer markets influence authors, how ideologies move across national boundaries, or how family structures affect reading practices.
If you’d like to read the entire abstract, you can get it here.