Paul A. Youngman, Mirsad Hadzikadic
May 22, 2014
by Pan Stanford
Reference - 304 Pages - 23 Color & 59 B/W Illustrations
ISBN 9789814463263 - CAT# N10976
For Librarians Available on CRCnetBASE >>
SAVE ~$15.00 on each
Questions of values, ontologies, ethics, aesthetics, discourse, origins, language, literature, and meaning do not lend themselves readily, or traditionally, to equations, probabilities, and models. However, with the increased adoption of natural science tools in economics, anthropology, and political science—to name only a few social scientific fields highlighted in this volume—quantitative methods in the humanities are becoming more common.
The theory of complexity holds significant promise for better understanding social and human phenomena based on interactions among the participating "agents," whatever they may be: a thought, a person, a conversation, a sentence, or an email. Such systems can exhibit phase transitions, feedback loops, self-organization, and emergent properties. These dynamic systems lend themselves naturally to the kind of analysis made possible by models and simulations developed with complex science tools. This volume offers a tour of quantitative analyses, models, and simulations of humanities and social science phenomena that have been historically the purview of qualitative methods.
"This volume makes a unique contribution in advancing the case for modeling in the humanities. Contemporary research is increasingly multidisciplinary and enriched by models that cross boundaries whenever dynamically similar phenomena emerge. Until recently, the humanities have stood outside of this development. This work documents pioneering explorations of models, networks, and methodological principles, most significantly, those that consolidate the conceptual, empirical, and practical aspects of inquiry within the humanities."
Prof. Marvin J. Croy, University of North Carolina at Charlotte, USA
"Being able to understand and explain complex ideas in the humanities and social sciences is increasingly important, given the current directions and pace of research and understanding in those fields. The works in this volume show that by applying quantitative methods, such as explanation through use of models, computer simulations, and artificial agents, not only is understanding of complexity assisted, but the visualization of complex phenomena, and the ability to explain and teach complex ideas, is now shown to be within the reach of researchers in fields previously not given to such techniques."
Prof. Charles D. Turnitsa, Columbus State University, USA