Universality reconsidered: Diversity in making meaning of facial expressions

open access articleIt has long been claimed that certain facial movements are universally perceived as emotional expressions. The critical tests of this Universality Thesis (UT) were conducted between 1969 and 1975 in small-scale societies in the Pacific using confirmation-based research methods. New studies conducted since 2008 have examine a wider sample of small-scale societies, including on the African and South American continents. They used more discovery-based research methods, providing an important opportunity for reevaluating the universality thesis. These new studies reveal diversity, rather than uniformity, in how perceivers make sense of facial movements, calling the universality thesis into doubt. Instead, they support a perceiver-constructed account of emotion perception that is consistent with the broader literature on perception

An Agent-Based Model of Collective Emotions in Online Communities

We develop a agent-based framework to model the emergence of collective emotions, which is applied to online communities. Agents individual emotions are described by their valence and arousal. Using the concept of Brownian agents, these variables change according to a stochastic dynamics, which also considers the feedback from online communication. Agents generate emotional information, which is stored and distributed in a field modeling the online medium. This field affects the emotional states of agents in a non-linear manner. We derive conditions for the emergence of collective emotions, observable in a bimodal valence distribution. Dependent on a saturated or a superlinear feedback between the information field and the agent's arousal, we further identify scenarios where collective emotions only appear once or in a repeated manner. The analytical results are illustrated by agent-based computer simulations. Our framework provides testable hypotheses about the emergence of collective emotions, which can be verified by data from online communities.Comment: European Physical Journal B (in press), version 2 with extended introduction, clarification

Efficient Resolution of Anisotropic Structures

We highlight some recent new delevelopments concerning the sparse representation of possibly high-dimensional functions exhibiting strong anisotropic features and low regularity in isotropic Sobolev or Besov scales. Specifically, we focus on the solution of transport equations which exhibit propagation of singularities where, additionally, high-dimensionality enters when the convection field, and hence the solutions, depend on parameters varying over some compact set. Important constituents of our approach are directionally adaptive discretization concepts motivated by compactly supported shearlet systems, and well-conditioned stable variational formulations that support trial spaces with anisotropic refinements with arbitrary directionalities. We prove that they provide tight error-residual relations which are used to contrive rigorously founded adaptive refinement schemes which converge in $L_2$. Moreover, in the context of parameter dependent problems we discuss two approaches serving different purposes and working under different regularity assumptions. For frequent query problems, making essential use of the novel well-conditioned variational formulations, a new Reduced Basis Method is outlined which exhibits a certain rate-optimal performance for indefinite, unsymmetric or singularly perturbed problems. For the radiative transfer problem with scattering a sparse tensor method is presented which mitigates or even overcomes the curse of dimensionality under suitable (so far still isotropic) regularity assumptions. Numerical examples for both methods illustrate the theoretical findings

Experiencing the world with archetypal symbols: A new form of aesthetics.

According to the theories of symbolic interactionism, phenomenology of perception and archetypes, we argue that symbols play the key role in translating the information from the physical world to the human experience, and archetypes are the universal knowledge of cognition that generates the background of human experience (the life-world). Therefore, we propose a conceptual framework that depicts how people experience the world with symbols, and how archetypes relate the deepest level of human experience. This framework indicates a new direction of research on memory and emotion, and also suggests that archetypal symbolism can be a new resource of aesthetic experience design.Postprint (published version

Reduced specificity of autobiographical memory and depression: The role of executive control

It has been widely established that depressed mood states and clinical depression, as well as a range of other psychiatric disorders, are associated with a relative difficulty in accessing specific autobiographical information in response to emotion-related cue words on an Autobiographical Memory Test (AMT; J. M. G. Williams & K. Broadbent, 1986). In 8 studies the authors examined the extent to which this relationship is a function of impaired executive control associated with these mood states and clinical disorders. Studies 1-4 demonstrated that performance on the AMT is associated with performance on measures of executive control, independent of depressed mood. Furthermore, Study 1 showed that executive control (as measured by verbal fluency) mediated the relationship between both depressed mood and a clinical diagnosis of eating disorder and AMT performance. Using a stratified sample in Study 5, the authors confirmed the positive association between depressed mood and impaired performance on the AMT. Studies 6-8 involved experimental manipulations of the parameters of the AMT designed to further indicate that reduced executive control is to a significant extent driving the relationship between depressed mood and AMT performance. The potential role of executive control in accounting for other aspects of the AMT literature is discussed. (PsycINFO Database Record (c) 2007 APA, all rights reserved)

Affective Man-Machine Interface: Unveiling human emotions through biosignals

As is known for centuries, humans exhibit an electrical profile. This profile is altered through various psychological and physiological processes, which can be measured through biosignals; e.g., electromyography (EMG) and electrodermal activity (EDA). These biosignals can reveal our emotions and, as such, can serve as an advanced man-machine interface (MMI) for empathic consumer products. However, such a MMI requires the correct classification of biosignals to emotion classes. This chapter starts with an introduction on biosignals for emotion detection. Next, a state-of-the-art review is presented on automatic emotion classification. Moreover, guidelines are presented for affective MMI. Subsequently, a research is presented that explores the use of EDA and three facial EMG signals to determine neutral, positive, negative, and mixed emotions, using recordings of 21 people. A range of techniques is tested, which resulted in a generic framework for automated emotion classification with up to 61.31% correct classification of the four emotion classes, without the need of personal profiles. Among various other directives for future research, the results emphasize the need for parallel processing of multiple biosignals

Geographic Clustering of Leishmaniasis in Northeastern Brazil1

Different forms of this disease are spreading rapidly in distinct geographic clusters in this region

How Our Personality Shapes Our Interactions with Virtual Characters - Implications for Research and Development

Abstract. There is a general lack of awareness for the influence of users´ personality traits on human-agent-interaction (HAI). Numerous studies do not even consider explanatory variables like age and gender although they are easily accessible. The present study focuses on explaining the occurrence of social effects in HAI. Apart from the original manipulation of the study we assessed the users ́personality traits. Results show that participants ´ personality traits influenced their subjective feeling after the interaction, as well as their evaluation of the virtual character and their actual behavior. From the various personality traits those traits which relate to persistent behavioral patterns in social contact (agreeableness, extraversion, approach avoidance, self-efficacy in monitoring others, shyness, public self-consciousness) were found to be predictive, whereas other personality traits and gender and age did not affect the evaluation. Results suggest that personality traits are better predictors for the evaluation outcome than the actual behavior of the agent as it has been manipulated in the experiment. Implications for research on and development of virtual agents are discussed