Alignment to the Actions of a Robot

Alignment is a phenomenon observed in human conversation: Dialog partners’ behavior converges in many respects. Such alignment has been proposed to be automatic and the basis for communicating successfully. Recent research on human–computer dialog promotes a mediated communicative design account of alignment according to which the extent of alignment is influenced by interlocutors’ beliefs about each other. Our work aims at adding to these findings in two ways. (a) Our work investigates alignment of manual actions, instead of lexical choice. (b) Participants interact with the iCub humanoid robot, instead of an artificial computer dialog system. Our results confirm that alignment also takes place in the domain of actions. We were not able to replicate the results of the original study in general in this setting, but in accordance with its findings, participants with a high questionnaire score for emotional stability and participants who are familiar with robots align their actions more to a robot they believe to be basic than to one they believe to be advanced. Regarding alignment over the course of an interaction, the extent of alignment seems to remain constant, when participants believe the robot to be advanced, but it increases over time, when participants believe the robot to be a basic version

Computational personality recognition in social media

A variety of approaches have been recently proposed to automatically infer users' personality from their user generated content in social media. Approaches differ in terms of the machine learning algorithms and the feature sets used, type of utilized footprint, and the social media environment used to collect the data. In this paper, we perform a comparative analysis of state-of-the-art computational personality recognition methods on a varied set of social media ground truth data from Facebook, Twitter and YouTube. We answer three questions: (1) Should personality prediction be treated as a multi-label prediction task (i.e., all personality traits of a given user are predicted at once), or should each trait be identified separately? (2) Which predictive features work well across different on-line environments? (3) What is the decay in accuracy when porting models trained in one social media environment to another

Genetic and Environmental Causes of Variation in Trait Resilience in Young People

The aim of this multi-informant twin study was to determine the relative role of genetic and environmental factors in explaining variation in trait resilience in adolescents. Participants were consenting families (N = 2,638 twins in 1,394 families), from seven national cohorts (age 12–18 years, both sexes) of monozygotic and dizygotic twins reared together. Questionnaire data on the adolescents’ Ego-resilience (ER89) was collected from mothers, fathers and twins, and analysed by means of multivariate genetic modelling. Variance in trait resilience was best represented in an ADE common pathways model with sex limitation. Variance in the latent psychometric resilience factor was largely explained by additive genetic factors (77% in boys, 70% in girls), with the remaining variance (23 and 30%) attributable to non-shared environmental factors. Additive genetic sources explained more than 50% of the informant specific variation in mothers and fathers scores. In twins, additive and non-additive genetic factors together explained 40% and non-shared environmental factor the remaining 60% of variation. In the mothers’ scores, the additive genetic effect was larger for boys than for girls. The non-additive genetic factor found in the twins’ self ratings was larger in boys than in girls. The remaining sex differences in the specific factors were small. Trait resilience is largely genetically determined. Estimates based on several informants rather than single informants approaches are recommended

Groups, organizations, families and movements: The sociology of social systems between interaction and society

Kühl S. Groups, organizations, families and movements: The sociology of social systems between interaction and society. Systems Research and Behavioral Science. 2020;37(3):496-515.In enhancing a proposal by Luhmann, this contribution shows that it is possible to locate different types of systems between ‘face‐to‐face‐interaction’ and ‘society’: groups, organizations, families and protest movements. The common ground of these is that they use membership to attribute persons to the system or not. However, they differ fundamentally in regard to how they understand membership. In contrast to Luhmann's differentiation between interaction, organization and society, it is not only possible to imagine different types of interlocking systems but also coequal combinations of and transitions between the different types of social systems

Measuring affective well-being at work using short-form scales : implications for affective structures and participant instructions

Measuring affective well-being in organizational studies has become increasingly widespread, given its association with key work-performance and other markers of organizational functioning. As such, researchers and policy-makers need to be confident that well-being measures are valid, reliable and robust. To reduce the burden on participants in applied settings, short-form measures of affective well-being are proving popular. However, these scales are seldom validated as standalone, comprehensive measures in their own right. In this article, we used a short-form measure of affective well-being with 10 items: the Daniels five-factor measure of affective well-being (D-FAW). In Study 1, across six applied sample groups (N = 2624), we found that the factor structure of the short-form D-FAW is robust when issued as a standalone measure, and that it should be scored differently depending on the participant instruction used. When participant instructions focus on now or today, then affect is best represented by five discrete emotion factors. When participant instructions focus on the past week, then affect is best represented by two or three mood-based factors. In Study 2 (N = 39), we found good construct convergent validity of short-form D-FAW with another widely used scale (PANAS). Implications for the measurement and structure of affect are discussed

Genomic analysis of family data reveals additional genetic effects on intelligence and personality

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