Recurrence-Based Analyses

Sebastian Wallot, Giuseppe Leonardi

• Publisher: SAGE Publications, Inc
• Year: 2024
• Print ISBN: 9781071872338
• eBook ISBN: 9781071872352
• Edition: 1
• Topic: Social Sciences
• Subtopic: Social Science Research & Methodology
• Index: Social Sciences

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.

Table of contents

• Cover
• Publisher Note
• Quantitative Applications in the Social Sciences
• Series: Quantitative Applications in the Social Sciences
• Half Title
• Acknowledgements
• Title Page
• Copyright Page
• Brief Contents
• Detailed Contents
• Series Editor Introduction
• Acknowledgments
• About the Authors
• Acronyms and Notation
• 1 What is Recurrence Analysis?
• 2 The Basics of Recurrence Analysis—Univariate RQA
• 3 The Bi-Variate Case: Cross-Recurrence Quantification Analysis
• 4 The Diagonal-Wise Cross-Recurrence Profile (DCRP)
• 5 Windowed Recurrence Analysis
• 6 Multivariate Analysis: Multidimensional Recurrence Quantification Analysis (MdRQA)
• 7 Sample Analysis and Practicalities
• 8 Conclusion
• References
• Index