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When Worldviews Collide: What Linguistic Style Matching and Distal Language Reveal About Deception in Political Discourse WHEN WORLDVIEWS COLLIDE: WHAT LINGUISTIC STYLE MATCHING AND DISTAL LANGUAGE REVEAL ABOUT DECEPTION IN POLITICAL DISCOURSE by Lucille M. Booker A Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Major: English The University of Memphis December 2012 UMI Number: 3570924 All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. UMI 3570924 Published by ProQuest LLC (2013). Copyright in the Dissertation held by the Author. Microform Edition © ProQuest LLC. All rights reserved. This work is protected against unauthorized copying under Title 17, United States Code ProQuest LLC. 789 East Eisenhower Parkway P.O. Box 1346 Ann Arbor, MI 48106 - 1346 Copyright © 2012 Lucille M. Booker All rights reserved ii Abstract Booker, Lucille, M. PhD. The University of Memphis. December 2012. When worldviews collide: What linguistic style matching and distal language reveal about deception in political discourse. Major Professor: Dr. Philip M. McCarthy. Political discourse is an observable, measurable, and testable manifestation of political worldviews. However, when worldviews collide, notions of truth and of lies are put to the test. The challenge for researchers is how to establish confidence in their analysis. Despite the growing interest in deception research from a diversity of fields and industries, the trend is to focus on validating the assessment approach to the data without considering validity issues related to the data itself. Such a trend is concerned more with how to assess linguistic features and less with what is being assessed. By contrast, this dissertation is concerned with both the how and what of deception analysis. Of necessity, establishing validity of the data needs to be addressed first. To this end, I use the computational textual analysis tool of the Gramulator to facilitate validating a corpus of truthful texts and deceptive texts written by self-described liberals and conservatives. Specifically, I apply the internal validity process (IVP) to the corpus. The IVP comprises rigorous validity assessments of the homogeneity and the markedness of the data as well as the derived indices. This process aims to validate what is being assessed (i.e., truthful texts and deceptive texts). I then use the Gramulator to analyze the corpus. Specifically, I conduct a linguistic style matching analysis and a distal language analysis of the corpus. The linguistic style matching analysis assesses the degree to which deceivers and truth tellers from divergent political groups coordinate their language. By contrast, the distal language analysis assesses the degree to which those same groups differ in their pronoun and pronominal usage. These analyses reveal how computational approaches in iii combination with linguistic theory facilitate deception analysis. The results of my dissertation suggest that the IVP supplies compelling evidence for the validity of the corpus. These results also suggest that linguistic style matching and distal language usage may be deception strategies used to influence others into a false belief. Taken as a whole, my dissertation offers greater insight into how subtle differences in the framing of word choices facilitate the identification of prominent features of deception in political discourse. iv Table of Contents Chapter Page 1 Introduction 1 Theme and Focus of the Dissertation 3 Research Question 5 Linguistic Style Matching 5 Distal Language 13 Overview of the Chapters 15 Relevance of the Dissertation 18 2 Literature Review 19 Background 19 Summaries 21 Deception Detection Studies in Behaviorism 23 DePaulo, Kashy, Kirkendol, Wyer, and Epstein (1996) 23 Approach 23 Experiment 24 Results 26 Summary 27 Burgoon and Qin (2006) 27 Approach 28 Experiment 28 Results 29 Summary 31 Broadhurst and Cheng (2005) 31 Approach 32 Experiment 32 Results 33 Summary 35 Summary of Deception Detection Studies in Behaviorism 36 Deception Detection Studies in NLP 37 Hancock, Thom-Santelli, and Ritchie (2004) 37 Approach 38 Experiment 39 Results 40 Summary 42 Zhou, Burgoon, Nunamaker, and Twitchell (2004) 42 Approach 43 Experiment 43 Results 45 Summary 45 v Carlson, George, Burgoon, Adkins, and White (2004) 46 Approach 46 Experiment 46 Results 47 Summary 48 Summary of Deception Studies in NLP 49 Deception Detection Studies in ANLP 50 Newman, Pennebaker, Berry, and Richards (2003) 50 Approach 51 Experiment 51 Results 53 Summary 55 Toma and Hancock (2010) 55 Approach 56 Experiment 56 Results 57 Summary 59 Duran, Hall, McCarthy, and McNamara (2010) 59 Approach 60 Experiment 60 Results 61 Summary 66 Duran, Hall, and McCarthy (2009) 66 Approach 67 Experiment 68 Results 68 Summary 73 Summary of Deception Detection Studies in ANLP 74 3 Review of The Gramulator 76 The Gramulator 76 Purpose: What does the Gramulator do? 76 Performance: How does the Gramulator work? 77 Platform: How do the module work? 78 Practice: What other studies use the Gramulator? 81 4 Methods 86 Mixed Methods Approach 86 The Experiment 86 Experimental Design 86 Survey 88 Amazon Mechanical Turk (MTurk) 91 vi The Corpus 95 Corpus Composition 95 Corpus Assessment 96 Pre-analysis Preparation 98 Method of Analysis 100 Contrastive Corpus Analysis 100 The Gramulator 101 Summary of Mixed Methods Approach 103 5 Validation 104 Theoretical Consideration 105 Measures, Metrics, and Indices 105 Measurement Validation 107 LIWC 109 Coh-Metrix 110 MTLD 110 LSA 111 In sum 112 Corpus Validation 112 Criteria for Establishing the Validity of a Corpus 115 Internal Validity Process (IVP) of the Gramulator 116 Internal Validity 116 The Six Assessments of the IVP 117 Homogeneity of Data 118 Homogeneity of Indices 118 Markedness Test of Index 118 Default Test of Data 119 Interpretation of the Results 119 Application 120 Data 121 Predictions 122 Results 123 TRUTH and LIE Results 123 FOR_IT and AGAINST_IT Results 125 Discussion 127 6 Linguistic Style Matching 129 Analysis 130 Corpus 130 Linguistic Style Matching Nomenclature 131 Typicals 132 Analysis 1: Are Liars Lying? 133 Hypothesis 1a: (L- # C+) > (L+ # C+) 133 Hypothesis 1b: (C- # L+) > (C+ # L+) 134 Hypothesis 2a: (C- # L+) > (C+ # L+) 134 Hypothesis 2b: (L- # C+) > (L+ # C+) 134 vii Predictions 134 Results 136 H1a and H1b: Stricter Gun Control Laws (A Liberal Issue) 137 H2a and H2b: Stricter Immigration Control Laws (A Conservative Issue) 138 Analysis 1: Discussion 139 Analysis 2: Are Conservative Liars More Convincing than Liberal Liars? 139 Hypothesis 3a: (C- # L+) > (L- # C+) 140 Hypothesis 3b: (C- # L+) > (L- # C+) 140 Prediction 140 Results 141 H3a: Stricter Gun Control Laws (A Liberal Issue) 142 H3b: Stricter Immigration Control Laws (A Conservative Issue) 142 Analysis 2: Discussion 142 General Discussion 143 7 Distal Language 145 Distal Language Nomenclature 145 Analysis 148 Analysis 1: Explicit Test of Distal Language Usage in a Lie Condition 150 Results 151 Analysis 2: Implicit Test of Distal Language Usage in a Lie Condition 152 Pronoun Results 154 Pronominal Results 155 General Discussion 158 8 Discussion 163 Overview 163 Motivation for the Dissertation 164 Experimental Approach 166 The Corpus 166 Analysis Tool 167 Analyses 167 Validation Approach 168 Validation Results 168 Linguistic Style Matching Approach 170 Linguistic Style Matching Results 171 Distal Language Approach 172 Distal Language Results 173 Interpretations 174 Implications 175 Relevance of the Dissertation 175 viii Limitations 179 Future Research 180 Conclusion 182 References 184 Appendix A. Survey 198 ix List of Tables Table Page 1. Representations of Analysis 1 (H1a, H1b, H2a, and H2b) 10 2. Representations of Analysis 2 (H3a and H3b) 12 3. The Corpora 96 4. Internal Validation Investigation 114 5. The Six Assessments of the Internal Validation Process (IVP) 117 6. TRUTH and LIE Results 124 7. FOR_IT and AGAINST_IT Results 125 8. Analysis 1: Results from the Evaluations of Hypotheses 1a, 1b, 2a, and 2b 136 9. Analysis 2: Results from the Evaluations of Hypotheses 3a and 3b 141 10. Fisher’s Exact Test: Independent Test Results 151 11. Fisher’s Exact Test: Paired Test Results 152 12. Pronoun and Pronominal Terms 153 13. Pronoun Assessment Results 154 14. Pronominals: LIE and TRUTH Assessment Results 156 15. Pronominals: Proximal and Distal Assessment Results 158 x Chapter 1: Introduction Deception research has advanced our understanding of a rather basic human behavior: lying in everyday life (DePaulo, Kashy, Kirkendol, Wyer, & Epstein, 1996). Intrinsic to understanding such a basic human behavior is context. That is, lying is a communicative norm and much can be understood about such a norm by assessing deception in context-specific social environments. This dissertation is concerned with such a task. More specifically, this dissertation is concerned with assessing deception within the social context of politics. To address such a concern, I conduct a deception analysis of political discourse. Political discourse is a repository of communications expressed by politicians, political groups, and the public, many of whom represent contrasting worldviews (Lakoff, 2002; van Dijk, 1998). When such worldviews collide, notions of truth and of lies are put to the test. In other words, the same instantiations of political discourse may be interpreted
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