Recent years have seen an explosion of interest in the use of computerized text analysis methods to address basic psychological questions. This comprehensive handbook brings together leading language analysis scholars to present foundational concepts and methods for investigating human thought, feeling, and behavior using language. Contributors work toward integrating psychological science and theory with natural language processing (NLP) and machine learning. Ethical issues in working with natural language data sets are discussed in depth. The volume showcases NLP-driven techniques and applications in areas including interpersonal relationships, personality, morality, deception, social biases, political psychology, psychopathology, and public health.
Table of Contents:
I. Introduction and Methods
1. Text Analysis for Psychology: Methods, Principles, and Practices, Brendan Kennedy, Ashwini Ashokkumar, Ryan L. Boyd, & Morteza Dehghani
II. Dyadic Synchrony/Psychological Coordination in Conversations
2. Language Coordination in Writing and Conversation, Molly E. Ireland & Taleen Nalabandian
3. Language in Close Relationships, Andrea B. Horn & Tabea Meier
4. Harnessing a Language Analysis Perspective to Uncover Emergent Group Processes, Aimée A. Kane & Lyn M. van Swol
5. Cooperation, Interaction, Search: Computational Approaches to the Psychology of Asking and Answering Questions, Christina M. Boyce-Jacino & Simon DeDeo
III. Political Psychology
6. Language Analysis in Political Psychology, Kayla N. Jordan
7. Automated Integrative Complexity: Language Analysis Tools for Psychological Research, Shannon C. Houck, Lucian Gideon Conway, III, & Alivia Zubrod
8. Text as Data in Political Psychology, Martijn Schoonvelde, Christian Pipal, & Gijs Schumacher
IV. Morality
9. Language Analysis in Moral Psychology, Mohammad Atari & Morteza Dehghani
10. Morality in Politics, Sze Yuh Nina Wang & Yoel Inbar
11. Morality in Language, Cristina Leone & Laura Niemi
V. Deception/Lying
12. Motivation for Deception, Paul J. Taylor, Grace McKenzie, & Ben Marshall
13. Lies and Language: A Context-Contingent Approach to Verbal Cues of Deceit, David M. Markowitz & Jeffrey T. Hancock
14. Deception and Its Detection, Judee K. Burgoon, Norah E. Dunbar, & Lee A. Spitzley
VI. Personality and Individual Differences
15. Investigating Individual Differences in Metaphor Use and Its Outcomes: Research Questions, Measurement, and Findings, Adam K. Fetterman, Katherine French, & Brian P. Meier
16. The Quantum Self: Examining Methodologies to Understand How Language Impacts Bilinguals’ Dual Selves, Shu Jiang & Nairán Ramírez-Esparza
17. Personality Disorder and Verbal Behavior, Charlotte Entwistle, Ely Marceau, & Ryan L. Boyd
VII. Affect/Sentiment
18. Behavioral Machine Intelligence with Language, Nikolaos Malandrakis, Victor Martinez, Anil Ramakrishna, Manoj Kumar, Karan Singla, Md Nasir, & Shrikanth Narayanan
19. Theory-Driven Measurement of Emotion (Expressions) in Social Media Text, William J. Brady, Killian McLoughlin, & M. J. Crockett
20. Identifying and Understanding the Targets of Sentiment Analysis, Charles Welch, Mahmoud Azab, & Rada Mihalcea
VIII. Public Health and Well-Being
21. The Language of Environmentalism: Harnessing Social Media Data in the Face of Environmental Uncertainty, Sonya Sachdeva
22. The Language of Mindfulness: Studying Contemplative Experience through Natural Language, Angelina J. Polsinelli, Deanna M. Kaplan, & Matthias R. Mehl
IX. Judgment/Biases
23. Knowledge, Cognition, and Everyday Judgment: An Introduction to the Distributed Semantics Approach, Russell Richie & Sudeep Bhatia
24. Sociolinguistic Properties of Word Embeddings, Alina Arseniev-Koehler & Jacob G. Foster
25. Social Biases in Word Embeddings and Their Relation to Human Cognition, Aylin Caliskan & Molly Lewis
26. Word Embeddings Reveal Social Group Attitudes and Stereotypes in Large Language Corpora, Tessa E. S. Charlesworth & Mahzarin R. Banaji
X. Ethical Guidelines
27. Ethical Pitfalls for Natural Language Processing in Psychology, Mark Alfano, Emily Sullivan, & Amir Ebrahimi Fard
28. Ethical Issues in Text Mining for Mental Health, Joshua August Skorburg & Phoebe Friesen
XI. Looking to the Horizon
29. Intergrouping and Aging Matters Textually, Howard Giles & Joseph B. Walther
30. Text and Discourse with Humans and Computers, Arthur C. Graesser & Leah C. Windsor
31. Computer-Based Language Analysis as a Paradigm Shift, James W. Pennebaker
Author Index
Subject Index
About the Author :
Morteza Dehghani, PhD, is Associate Professor of Psychology and Computer Science and a member of the faculty of the Brain and Creativity Institute at the University of Southern California. Dr. Dehghani's research relies on machine learning and natural language processing to explore cognitive and psychological traces in artifacts of social discourse. Specifically, he investigates properties of moral cognition by analyzing language in conjunction with behavioral studies. Dr. Dehghani is a recipient of a CAREER Award from the National Science Foundation and a Young Investigator Award from the Air Force Office of Scientific Research.
Ryan L. Boyd, PhD, is Assistant Professor of Behavioral Analytics at Lancaster University in the United Kingdom, holding shared appointments in the Department of Psychology, Security Lancaster, and the Data Science Institute. His research interests broadly revolve around how our motives are revealed in language--that is, how our everyday words provide clues to why we think, feel, and behave in the ways that we do. Dr. Boyd’s research spans topics ranging from personality to society, mental health, human sexuality, and storytelling. He has authored dozens of free, open-source text analysis programs for social scientists, and he has been involved in the development of Linguistic Inquiry and Word Count since 2015. Dr. Boyd is on the editorial boards at PLOS ONE and Frontiers in Artificial Intelligence: Language and Computation, and is a member of the advisory board for Psychology of Language and Communication.
Review :
"Language provides a richer, more detailed window into the human experience than any other source of data, and large-scale computational techniques have created unprecedented opportunities in the study of human psychology. This volume provides a comprehensive examination of language analysis methods and how they are being used across an astonishing range of psychological research. It will be highly valuable to students and scholars in psychology who are seeking a relevant, up-to-date overview of text analysis methods. Conversely, this book also represents an invitation to computational folks to better understand the nature of psychological research questions and the ways that their text analysis expertise can help advance understanding of what makes people tick."--Philip Resnik, PhD, Department of Linguistics and Institute for Advanced Computer Studies, University of Maryland, College Park
"The accelerating growth of new computational methods, theories, and applications in language analysis opens up exciting possibilities for researchers, but it can also be daunting if you are entering the field or trying to keep up to speed. But never fear! Dehghani and Boyd have brought together a formidable crew of experts to create an accessible guide to the latest developments in language analysis. This book is an ideal text for a graduate course, and can serve as a reference and source of inspiration for researchers."--Sanjay Srivastava, PhD, Department of Psychology, University of Oregon
"This handbook assembles many of the best researchers who quantitatively analyze language to better understand people. The coverage is impressively broad, from personality to politics, from conversations and deception to the language of affect and morality. The methods used are equally broad, from the use of classical lexica to modern vector embedding methods. This book is ideal for a graduate seminar in psychology or related fields on the ways in which language analysis is yielding insights into human thought, behavior, and communication."--Lyle Ungar, PhD, Department of Computer and Information Science, University of Pennsylvania-Highly recommended. Graduate students, faculty, and professionals.--Choice Reviews, 4/1/2023
