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I NTRODUCTION R ELATED W ORKS M ODEL E XPERIMENTS C ONCLUSION The role of emotion on communication and attitude dynamics: an agent-based approach Kei-Lo Brousmiche 1 , 3 Jean-Daniel Kant 2 Nicolas Sabouret 2 Stephane Fournier 3 Franois

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INTRODUCTION RELATED WORKS MODEL EXPERIMENTS CONCLUSION

The role of emotion on communication and attitude dynamics: an agent-based approach

Kei-Léo Brousmiche1,3 Jean-Daniel Kant2 Nicolas Sabouret2 Stephane Fournier3 François Prenot-Guinard3

1LIP6 - Université Pierre & Marie Curie, Paris, France 2LIMSI-CNRS - Université Paris-Sud, Orsay, France 3Airbus Defense & Space, Elancourt, France

WCSS, Sao Paulo, november 2014

kei-leo.brousmiche@lip6.fr LIP6, Airbus D&S, LIMSI 1

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INTRODUCTION RELATED WORKS MODEL EXPERIMENTS CONCLUSION

Definitions

Attitude

“a psychological tendency that is expressed by evaluating a particular entity with some degree of favor or disfavor” [Eagly and Chaiken, 1993] Simple version: How much do I like something, or not. [Me, 2014]

Belief

Acceptation of a factual information [Oxford Dictionary]

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Context: Stabilization Operations

Needs for new systems Population-centric training systems Perception-attitude-behaviour dynamics toward Forces Social simulation Attitude dynamics Agent-based modelling

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INTRODUCTION RELATED WORKS MODEL EXPERIMENTS CONCLUSION

Objectives

Model of attitude dynamics based on Psychological theories Representation of beliefs Interest of information Generic Model of communication Belief exchange Social network Inter-ethnic conflicts Model social groups

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Classical Attitude Models in Social Simulation

Simple models e.g binary, discrete or real values [Nowak et al., 1990] ✪ Do not consider the construction mechanism of the attitude [Urbig and Malitz, 2007] ✦ Sum of the evaluations of the object’s features ✪ Bounded-confidence model ⇒ attitude-beliefs connections are lost ✪ Agents shouldn’t have unlimited memory

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INTRODUCTION RELATED WORKS MODEL EXPERIMENTS CONCLUSION

An Attitude Models in Psychology

Attitude as object-evaluation associations [Fazio, 2007] ✦ Links between attitude and beliefs ✦ Limited memory with varying accessibilies

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INTRODUCTION RELATED WORKS MODEL EXPERIMENTS CONCLUSION

Communication

What to communicate? Attitude itself [Xia et al., 2010, Castellano et al., 2009] Or part of [Urbig and Malitz, 2007] ✪ no psychological foundation ✌ daily communication: conversational narratives > 40% [Eggins and Slade, 1997] ✇ Belief exchange How? ✇ Based on the narrative interest of the belief [Dimulescu and Dessalles, 2009] To whom? Small-world [Milgram, 1967] Social groups

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General Principle

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INTRODUCTION RELATED WORKS MODEL EXPERIMENTS CONCLUSION

Agent Cognition

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Cognition Revision

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Acquire beliefs

Revise attitudes

Communicate beliefs Information’s interest: Dessalles’ Simplicity Theory [Dimulescu and Dessalles, 2009]

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INTRODUCTION RELATED WORKS MODEL EXPERIMENTS CONCLUSION

Information’s Interest

Interest of

Retention: information’s accessibility in memory Narration: communication probability

Simplicity Theory [Dimulescu and Dessalles, 2009]

INT(a) = 2E(a)+S(a) E(a): Emotional response S(a): Generated surprise

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Simplicity Theory: Emotional Response

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Weber-Fechner’s law of the stimulus: E(a) = log

1 + |stimulus|

ξ

stimulus = payoff of the action’s impact

ξ sensibility parameter

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INTRODUCTION RELATED WORKS MODEL EXPERIMENTS CONCLUSION

Simplicity Theory: Surprise

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S = Uraw − Uperso Uraw raw unexpectedness Uperso personal unexpectedness

n multiple dimensions:

Utime, Usocial, Ugeo Ux = Cx

w − Cx d

x the dimension Cx

w complexity of generation

Cx

d complexity of description

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Simplicity Theory: Example of Time Complexity

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Raw unexpectedness Ctime

w

= log(date(a) − date(aold)) ≈ rarity Ctime

d

= log(t − date(a)) ≈ recency ✇ Utime

raw (a) = log

date(a)−date(aold)

t−date(a)

Personal Unexpectedness:

✇ Utime

perso(a) = log

date(a)−date(aperso)

t−date(a)

Surprise (Utime

raw (a) − Utime perso(a)):

✇ Stime(a) = log

date(a)−date(aold)

date(a)−date(aperso)

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INTRODUCTION RELATED WORKS MODEL EXPERIMENTS CONCLUSION

Attitude construction

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INTRODUCTION RELATED WORKS MODEL EXPERIMENTS CONCLUSION

Analysis of narrative interest components’ impacts

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100 agents ; repeated actions ; introduction of α to weight the surprise factor → Boosting effect and habituation effect

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The impact of social groups

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100 agents ; 3 social groups ; 3 phases of repeated actions

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Conclusion

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An attitude dynamics model based on socio-psychological theories beliefs narrative communication emotion Futur works real case study calibration

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References I

Castellano, C., Fortunato, S., and Loreto, V. (2009). Statistical physics of social dynamics. Reviews of modern physics, 81(2):591. Dimulescu, A. and Dessalles, J.-L. (2009). Understanding narrative interest: Some evidence on the role of unexpectedness. In Proceedings of the 31st Annual Conference of the Cognitive Science Society, pages 1734–1739. Eagly, A. H. and Chaiken, S. (1993). The psychology of attitudes. Harcourt Brace Jovanovich College Publishers. Eggins, S. and Slade, D. (1997). Analysing casual conversation. Equinox Publishing Ltd. Fazio, R. H. (2007). Attitudes as object-evaluation associations of varying strength. Social Cognition, 25(5):603.

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References II

Milgram, S. (1967). The small world problem. Psychology today, 2(1):60–67. Nowak, A., Szamrej, J., and Latane, B. (1990). From private attitude to public opinion: A dynamic theory of social impact. Psychological Review, 97(3):362. Urbig, D. and Malitz, R. (2007). Drifting to more extreme but balanced attitudes: Multidimensional attitudes and selective exposure. ESSA, Toulouse. Xia, H., Wang, H., and Xuan, Z. (2010). Opinion dynamics: Disciplinary origins, recent developments, and a view on future trends.

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