About the Book
This book covers the science of measuring the invisible building blocks of thought processes that are useful for understanding humans, including technology users, media consumers, and consumers of goods and services. It brings together key notions from the psychometric tradition of measuring attitudes, couples them with findings of studies that have investigated what works and what doesn’t work when using self-report measures in the context of surveys and experiments and explains and connects the preceding in a non-technical manner. This book also extends what we have learned from over 100 years of self-report measurement science for extracting opinion from social media text content and the potential role that AI can play in assisting opinion extraction.
This book provides:
- An explanation of what self-report measurement entails for beginners.
- A clear set of assumptions that need to be made in order for self-report measurement to provide the researcher with valuable information.
- A set of principles of sound self-report measurement practice based on science that relates to the assumptions that are needed.
- A mindset that can be used by researchers using self-report measurement in the contexts of surveys and experiments and another mindset that can be used by those who are trying to extract opinion from social media text content.
- A roadmap for quantifying the errors associated with self-report measurement.
Contents
Preface 1
Chapter 1: An intuitive need to measure the invisible for understanding thoughts, feelings, and behaviors 5
Chapter 2: Measuring the invisible: Practical uses and function within the method of science 18
Chapter 3: From observing behaviors to conceptualizing self-report measurement and developing a measurement mindset 25
Chapter 4: What can a researcher do to meet the self-report measurement assumptions? 56
Chapter 5: Principles and expectations: Statement content and placement 60
Chapter 6: Principles and expectations: Response category characteristics 77
Chapter 7: Principles and expectations: Motivation to self-report 96
Chapter 8: Principles and expectations: Respondent abilities 128
Chapter 9: A road map for quantifying the errors stemming from violations of the principles of self-report measurement: The Red Flags Approach (RFA) 152
Chapter 10: Implications for extracting self-report measurement from social media text content – What role can Artificial Intelligence (AI) play? 178
Chapter 11: A recap and some notes on the relevance of self-report measurement in the age of Artificial Intelligence (AI) 208
List of Figures 211
List of Tables 213
Index 215