Social signals: a framework in terms of goals and beliefs

Is It Me or the Robot? A Critical Evaluation of Human Affective State Recognition in a Cognitive Task

A key goal in human-robot interaction (HRI) is to design scenarios between humanoid robots and humans such that the interaction is perceived as collaborative and natural, yet safe and comfortable for the human. Human skills like verbal and non-verbal communication are essential elements as humans tend to attribute social behaviors to robots. However, aspects like the uncanny valley and different technical affinity levels can impede the success of HRI scenarios, which has consequences on the establishment of long-term interaction qualities like trust and rapport. In the present study, we investigate the impact of a humanoid robot on human emotional responses during the performance of a cognitively demanding task. We set up three different conditions for the robot with increasing levels of social cue expressions in a between-group study design. For the analysis of emotions, we consider the eye gaze behavior, arousal-valence for affective states, and the detection of action units. Our analysis reveals that the participants display a high tendency toward positive emotions in presence of a robot with clear social skills compared to other conditions, where we show how emotions occur only at task onset. Our study also shows how different expression levels influence the analysis of the robots' role in HRI. Finally, we critically discuss the current trend of automatized emotion or affective state recognition in HRI and demonstrate issues that have direct consequences on the interpretation and, therefore, claims about human emotions in HRI studies.

PeppeRecycle: Improving Children’s Attitude Toward Recycling by Playing with a Social Robot

In this paper, we investigate the use of a social robot as an engaging interface of a serious game intended to make children more aware and well disposed towards waste recycle. The game has been designed as a competition between the robot Pepper and a child. During the game, the robot simultaneously challenges and teaches the child how to recycle waste materials. To endow the robot with the capability to play as a game opponent in a real-world context, it is equipped with an image recognition module based on a Convolutional Neural Network to detect and classify the waste material as a child would do, i.e. by simply looking at it. A formal experiment involving 51 primary school students is carried out to evaluate the effectiveness of the game in terms of different factors such as the interaction with the robot, the users’ cognitive and affective dimensions towards ecological sustainability, and the propensity to recycle. The obtained results are encouraging and draw promising scenarios for educational robotics in changing children’s attitudes toward recycling. Indeed Pepper turns out to be positively evaluated by children as a trustful and believable companion and this allows children to be concentrated on the “memorization” task during the game. Moreover, the use of real objects as waste items during the game turns out to be a successful approach not only for perceived learning effectiveness but also for the children’s engagement.

Effects of Self-Expressive Brand and Susceptibility to Interpersonal Influence on Brand Addiction: Mediating Role of Brand Passion

Although the concept of the consumer–brand relationship has undergone rapid change over the past two decades, the issue of brand addiction is still generally neglected in the literature. Based on social identity theory, the research develops a conceptual model of the influence of self-expressive brands (SEBs) and susceptibility to interpersonal influence (SUSCEP) on brand addiction. The results of this research demonstrate both separate and joint effects of SEBs and SUSCEP on brand addiction. In addition, harmonious brand passion and obsessive brand passion positively mediate the relationships among SEB, SUSCEP, and brand addiction. The research explores the formation mechanism of brand addiction from a new perspective and has important practical implications for brand marketers concerned with finding the most effective means to enhance the consumer–brand relationship.

Social signals: from theory to applications

The Special Issue Editorial introduces the research milieu in which Social Signal Processing originates, by merging computer scientists and social scientists and giving rise to this field in parallel with Human-Computer Interaction, Affective Computing, and Embodied Conversational Agents, all similarly characterized by high interdisciplinarity, stress on multimodality of communication, and the continuous loop from theory to simulation and application. Some frameworks of the cognitive and social processes underlying social signals are identified as reference points (Theory of Mind and Intersubjectivity, mirror neurons, and the ontogenesis and phylogenesis of communication), while three dichotomies (automatic vs. controlled, individualistic vs. intersubjective, and meaning vs. influence) are singled out as leads to navigate within the theoretical and applicative studies presented in the Special Issue.