Recurrence-Based Analyses - Couverture souple

Sebastian Wallot; Giuseppe Leonardi

 
9781071872338: Recurrence-Based Analyses

Synopsis

This book introduces techniques developed in physics and physiology for characterizing and analyzing patterns in time series data to a broad audience of social scientists. In contrast to time-series regression and related techniques, recurrence quantification analysis (RQA) has its background in chaos and nonlinear dynamical systems—theory arguably very relevant to social processes. The goal of Recurrence-Based Analyses is to introduce readers to these techniques that can characterize a system’s complexity, stability and instability, and conditions under which it transitions from one state to another. The authors illustrate concepts and techniques with relevant social science examples at different temporal scales: biweekly polling data on federal elections in Germany; daily values of three stock market indices; daily cases of SarsCov-19 in four countries during the pandemic; and second-by-second vocalizations of mothers and infants interacting recorded by motion cameras. This introduction to RQA serves as a useful supplement to undergraduate and graduate courses in computational social science, and also by researchers who seek new tools to address social scientific questions in new ways.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

À propos des auteurs

Sebastian Wallot obtained his diploma in psychology from the University of Trier (Germany) and his PhD in experimental psychology from the University of Cincinnati, OH (USA). After postdoctoral positions at the University of Aarhus (Denmark) and the Max Planck Institute for Empirical Aesthetics in Frankfurt at the Main (Germany), he is currently working as Professor for research methods in psychology at Leuphana University of Lüneburg (Germany). His research if focused on joint action and reading from a dynamic systems perspective. Moreover, he is developing new analysis tools for time series – particularly in the area of recurrence and fractal analysis.



Giuseppe Leonardi obtained his MA degree in psychology from the University of Padua (Italy) and his PhD in experimental psychology at the University of Trieste (Italy). As a visiting student he was at the Center for Complex Systems at Florida Atlantic University (USA). His interests gradually focused on a dynamical approach in behavioral interactions and the methodological challenges this new approach requires. He especially concentrated on RQA and its applications to human language and cooperative behavior. From 2017 he has been at the University of Economics and Human Sciences in Warsaw (Poland), where he serves as dean of the School of Human Sciences since 2019.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.