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The Information in Emotion Communication Alison Duncan Kerr Kevin Scharp Version 1.6 13 Feb 2020 94,164 words The Information in Emotion Communication Kerr & Scharp Contents List of Figures iii Acknowledgements v Introduction 1 0.1: Emotions 2 0.2: Emotion Communication 3 0.3: Information 5 0.4: Social Media 6 0.5: Emotion Security 7 0.6: Plan 8 Chapter 1: Emotion Communication Systems 10 1.1: Emotions in Individuals 10 1.2: Emotions as Social 13 1.3: Emotion Communication 14 1.4: Animal Communication Science 16 1.5: Theory of Mind (ToM) in Psychology 21 1.6: Affective Sciences 28 1.7: Artificial Intelligence and Computational Theories of Emotion 30 1.8: Emotion Contagion 34 1.9: Emotions as Social Information 35 1.10: Summary of Research on Emotion Communication 39 1.11: Extensions 40 Chapter 2: Emotion Signal Systems 44 2.1: Signal Systems 46 2.2: Emotion Signal Systems 48 2.3: Are Emotion Signal Systems Conventional? 52 2.4: Ekman’s Seven Kinds of Information in Emotion Communication 54 2.5: What is the Message? 56 2.6: Signal Theory vs Contagion Theory 61 2.7: The Problem of Communication with Unfitting Emotions 64 2.8: Scarintino’s Theory of Affective Pragmatics 67 2.9: Emotional Implicature 74 2.10: Extensions 76 Chapter 3: Emotion Communication Channels 79 3.1: Information Theory 79 3.2: Channels 80 3.3: Information Measures for Channels 85 3.4: Basic Emotion Communication Channel 92 3.5: Extensions 94 Chapter 4: Coded Emotion Communication Channels 96 4.1: Encoding and Decoding Messages 96 4.2: Information Measures for Coded Channels 98 4.3: Compression and Error Correction 99 4.4: Basic Coded Emotion Communication Channel 105 4.5: Information Theory and Biology 106 4.6: Extensions 108 i The Information in Emotion Communication Kerr & Scharp Chapter 5: Basic Emotion Communication Networks 110 5.1: Mathematics of Networks 111 5.2: Structural Network Measures 112 5.3: Network Information Theory 115 5.4: Information Theoretic Results: Channels vs Networks 125 5.5: Animal vs Register Interpretation of Nodes 126 5.6: Qualitative Simple Emotion Communication Network 136 5.7: Emotion Elicitation Channels 138 5.8: Emotion Pre-Appraisal Channel 140 5.9: Emotion Post-Appraisal Channel 140 5.10: Emotion Indirect Elicitation Channel 141 5.11: Complex Nodes 141 5.12: Quantitative Emotion Communication Network 148 5.13: Extensions 150 Chapter 6: Advanced Emotion Communication Networks 152 6.1: Emotion Expression, Perception, Elicitation, and Appraisal 153 6.2: Emotion Regulation 155 6.3: Quantitative Interpersonal Emotion Regulation (QIER) 157 6.4: Emotion Communication and Theory of Theory of Mind (ToToM) 160 6.5: Eavesdropping and Emotion Encryption 163 6.6: Deception 165 6.7: Reliability 167 6.8: Contagion Channels and Networks 171 6.9: Courage and other Virtues 174 6.10: Using Emotion Taxonomies to Code Messages 175 6.11: Complex Networks 178 6.12: Multi-Layer Networks 182 6.13: Qualitative Emotion Communication System 186 6.14: Quantitative Emotion Communication Multi-Layer Network 189 6.15: The Social Media Influence Factor 199 6.16: Extensions 203 Chapter 7: Emotions on Social Media 207 7.1: Social Media 208 7.2: The Information Theory of Social Media 212 7.3: Emotional Effects of Social Media 214 7.4: You are in an Abusive Relationship 217 7.5: Artificial Emotion Recognition 220 7.6: Information Theory of Artificial Emotion Recognition 222 7.7: Emotion Recognition Jamming 223 7.8: Advertising, Propaganda, and Coordinated Inauthentic Behaviour 224 7.9: Surveillance Capitalism 231 7.10: Cambridge Analytica 232 7.11: Russian Active Measures and the Current Cyberwar 246 7.12: Extensions 264 Chapter 8: Emotion Network Security 271 8.1: Information Security and Encryption 272 8.2: Information Flow 273 8.3: Network Control Jamming 276 ii The Information in Emotion Communication Kerr & Scharp 8.4: Statistical Mechanics: The Ising Model 285 8.5: Emotion Security on Social Media 293 Conclusion 301 Work Cited 305 iii The Information in Emotion Communication Kerr & Scharp List of Figures Chapter 1 1: Causal interactions among emotions and other states 26 2: BToM kinds of reasoning in emotion attribution 27 3: Data types for computational theories of emotion 33 Chapter 2 4: Emotion Signal System 49 5: Emotions and their expression in different modalities 51 6: Kinds of Pragmatic Phenomena 77 Chapter 3 7: Lion and Cheetah incomplete joint probability distribution 82 8: Lion and Cheetah joint probability distribution 1 83 9: Lion and Cheetah joint probability distribution 2 83 10: Lion and Cheetah joint probability distribution 3 84 11: Basic emotion communication channel 93 Chapter 4 12: Coded emotion communication channel 106 Chapter 5 13: Four independent channels among two sources and two destinations 116 14: A communication network with two sources and two destinations 116 15: Array of sixteen probability combinations for four variables. 117 16: Example probability distribution for lion, bear, cheetah, and rabbit 118 17: Projected matrix probability distribution for lion and bear. 119 18: Option 1 for interpreting a network – “Animal” interpretation 128 19: Option 2 for interpreting a network – “Register” interpretation 129 20: Network with multiple receiving animals 130 21: Coded emotion network – “Animal” interpretation 131 22: Coded emotion network – “Register” interepretation 132 23: Qualitative Simple Emotion Communication System 137 24: Direct emotion elicitation channel 138 25: Multi-channel direct elicitation network 139 26: Indirect emotion elicitation channel 141 27: Complex node with registers and indirect elicit 143 28: Complex node with appraisal, registers, and indirect elicit 145 29: Complex node with integrated appraisal and communication 147 30: Quantitative simple emotion communication network 149 Chapter 6 31: Emotion research topics plotted on emotion communication node 154 32: Interpersonal emotion regulation processes 159 33: Direct reliability network 168 34: Dual hierarchy of reliability assessments 170 35: Contagion channels of varying complexity 173 36: Valence/arousal emotion taxonomy 176 37: A two-person cyclic network with complex nodes and integrated inputs 180 38: Qualitative complex emotion communication system 187 39: Three layers of complex emotion communication system 188 40: Three-person cyclic emotion communication network with complex nodes 191 iv The Information in Emotion Communication Kerr & Scharp 41: Structural features of emotion communication multi-layer network 196 Chapter 7 42: Daily time spent on social media worldwide 211 43: Emotion communication stages in the development of humanity 216 44: EQ-Radio system of remote emotion recognition 222 45: SCL and Cambridge Analytica Companies and Shareholders 235 46: Emerdata Limited and Cambridge Analytica 237 47: Diagram of the OCEAN model of personality 239 48: Accuracy of personality trait predictions from Facebook likes 240 49: Accuracy of OCEAN personality component predictions from Facebook likes 241 50: Layers of the Russian Attack on the 2016 US Presidential Election 247 Chapter 8 51: Ising model near critical temperature 288 52: Ising model at low temperature 289 53: Ising model at high temperature 290 54: Ising model with external field 290 v The Information in Emotion Communication Kerr & Scharp Acknowledgements For Nola, Pia, and Jasper. Immense joy. Thank you to our families for their unwavering support. And, to each other. vi The Information in Emotion Communication Kerr & Scharp Introduction 0.1: Emotions 2 0.2: Emotion Communication 3 0.3: Information 5 0.4: Social Media 6 0.5: Emotion Security 7 0.6: Plan 8 It hardly needs to be stressed how important emotions are to human life and to the lives of so many animals around us. Humanity has had a complicated past with its emotions, but the previous century of inquiry has seen remarkable scientific understanding of what emotions are, how they work, and what they do for us. A huge amount of that work has been on emotions as episodes that happen to individuals. So much has been learned on this front, and we applaud this research. We, however, follow a growing trend of looking at how emotions function in groups of animals as a system of communication. This too has been known for a long time, but the novel aspect of our approach is that we provide a quantitative theory of how information is transferred in groups of animals by virtue of their emotions and emotional capacities, like the ability to detect emotion behavior (e.g., fighting something), the ability to detect emotions on the basis of detecting behavior (e.g., fear) and the ability to express emotions in behavior. The theory presented here provides answers to questions about how much information is transferred from one point to another, or through a node in a network, or through an entire layer of a complex network. Although the theory presented here is quantitative, the mathematics involved is not complicated, and we work out many examples along the way. Most chapters end with a sequence of points for further research and a list of references. Being able to put numbers to the information passed in emotion communication opens up entire new vistas of research directions. Evolutionary theory has long been connected to various quantitative measures of information in animal communication systems, so this theory 1 The Information in Emotion Communication Kerr & Scharp ought to mesh well with contemporary evolutionary theory on emotions.1 It supplants the “contagion” theory of emotion transmission, and it subsumes areas of active research like emotion elicitation, emotion expression, and interpersional emotion regulation. Even more important is that a quantitative theory of emotional information is badly needed to combat the vast emotion manipulation occurring online in social media. We know about many of these kinds of manipulations, and the information theory of emotion communication provides one with an array of technological and quantitative tools to detect and combat large-scale emotion manipulation on social media.
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