Masked emotional priming beyond global valence activations

An immense body of research demonstrates that emotional facial expressions can be processed unconsciously. However, it has been assumed that such processing takes place solely on a global valence-based level, allowing individuals to disentangle positive from negative emotions but not the specific emotion. In three studies, we investigated the specificity of emotion processing under conditions of limited awareness using a modified variant of an affective priming task. Faces with happy, angry, sad, fearful, and neutral expressions were presented as masked primes for 33 ms (Study 1) or 14 ms (Studies 2 and 3) followed by emotional target faces (Studies 1 and 2) or emotional adjectives (Study 3). Participants’ task was to categorise the target emotion. In all three studies, discrimination of targets was significantly affected by the emotional primes beyond a simple positive versus negative distinction. Results indicate that specific aspects of emotions might be automatically disentangled in addition to valence, even under conditions of subjective unawareness.     

The Relation Between Social Identities and Outgroup Hostility Among German Immigrant-Origin Citizens

One of the major drivers of societal conflict are the intergroup relations which rely mainly on social identity and which are rarely analyzed for immigrant groups. This article changes this point of view by investigating the extent to which national, ethnic, and religious identities relate to outgroup hostilities towards the majority of the German population, towards other immigrant groups, and towards Syrian refugees among immigrant-origin citizens. We employ a theoretical framework based on the social identity approach and use new representative survey data from 2017 for Germans of Turkish descent (N = 480) and Russian Germans (N = 471). Based on multivariate linear regression analysis, we show that ethnic identity has the strongest positive relation with outgroup hostilities, with the exception of the Russian-Germans' evaluation of the German majority population. National identity among Germans of Turkish descent lessens their hostility towards other immigrants. Our results show the importance of analyzing immigrant groups with different migration trajectories separately before making generalized claims. Not only are the identity relations different between an ingroup identification and various outgroup targets, but they are also different between the immigrant groups for the same ingroup identification and outgroup target.     

Adaptations in driver deceleration behaviour with automatic incident detection: A naturalistic driving study

Traffic congestion and crash rates can be reduced by introducing variable speed limits (VSLs) and automatic incident detection (AID) systems. Previous findings based on loop detector measurements have revealed that drivers reduce their speeds while approaching traffic congestion when the AID system is active. Notwithstanding these behavioural effects, most microscopic traffic flow models assessing the impact of VSLs do not describe driver response accurately.This study analyses the main factors that influence driver deceleration behaviour while approaching traffic congestion with and without VSLs. The Dutch VSL database was linked to the driver behaviour data collected in the UDRIVE naturalistic driving study. Driver engagement in secondary tasks and glance behaviour were extracted from the video data. Linear mixed-effects models predicting the characteristics of deceleration events were estimated.The results show that the maximum deceleration is high when approaching a slower leader, when driving at high speeds and short distance headways, and close to the beginning of traffic congestion. The minimum time headway is short when driving at high speeds and changing lanes. Certain drivers showed higher decelerations and shorter time headways than others. Controlled for these main factors, smaller maximum decelerations were found when the VSLs were present and visible, and when the gantries were within close proximity. These factors could be incorporated into microscopic traffic simulations to evaluate the impact of AID systems on traffic congestion more realistically. Further research is needed to clarify the link between engagement in secondary tasks, glance behaviour and deceleration behaviour.     

How Should a Speech Recognizer Work?

Although researchers studying human speech recognition (HSR) and automatic speech recognition (ASR) share a common interest in how information processing systems (human or machine) recognize spoken language, there is little communication between the two disciplines. We suggest that this lack of communication follows largely from the fact that research in these related fields has focused on the mechanics of how speech can be recognized. In Marr's (1982) terms, emphasis has been on the algorithmic and implementational levels rather than on the computational level. In this article, we provide a computational-level analysis of the task of speech recognition, which reveals the close parallels between research concerned with HSR and ASR. We illustrate this relation by presenting a new computational model of human spoken-word recognition, built using techniques from the field of ASR that, in contrast to current existing models of HSR, recognizes words from real speech input.     

Stereotype activation is unintentional: Behavioural and event‐related potenials evidence

In this study, a priming Stroop paradigm was used to determine whether stereotype activation is unintentional. Priming conditions (priming/no‐priming) and the relationship between priming and target (consistent/inconsistent/no‐relation) were the independent variables; accuracy, reaction time and N400 amplitude were used as dependent variables. The reaction time revealed that stereotype activation is, to some extent, unintentional. Furthermore, the event‐related potenial (ERP) results showed that N400 amplitude was larger for inconsistent conditions than for consistent conditions. This result supported the notion that stereotype activation is an unintentional and automatic process.     

Cognitions as mediators in the relationship between self-compassion and affect

Previous studies suggest that self-compassion is related to numerous facets of mental health, but the role of cognitions in this relationship remains unknown. To examine the mediating role of cognitions in the relationship between self-compassion and anxiety, depression, and life satisfaction when controlling for self-esteem in Japanese people, we conducted two studies. Study 1 (N = 231) examined the relationship between self-compassion and affect by modeling negative automatic thoughts as a mediator; Study 2 (N = 233) tested whether positive and negative automatic thoughts meditate this relationship. Results suggested that both self-compassion and self-esteem increased positive automatic thoughts and decreased trait anxiety, whereas only self-esteem increased life satisfaction and decreased depression directly. Positive automatic thoughts increased life satisfaction and decreased depression and trait anxiety, and positive automatic thoughts mediated the relationship between self-compassion and negative affect. These findings suggest that both positive and negative automatic thoughts mediate the relationship between self-compassion and affect in Japanese people.     

Does change in ethical education influence core moral values? Towards history- and culture-aware morality model with application in automatic moral reasoning

In this study, we focus on ethical education as a means to improve artificial companion’s conceptualization of moral decision-making process in human users. In particular, we focus on automatically determining whether changes in ethical education influenced core moral values in humans throughout the century. We analyze ethics as taught in Japan before WWII and today to verify how much the pre-WWII moral attitudes have in common with those of contemporary Japanese, to what degree what is taught as ethics in school overlaps with the general population’s understanding of ethics, as well as to verify whether a major reform of the guidelines for teaching the school subject of “ethics” at school after 1946 has changed the way common people approach core moral questions (such as those concerning the sacredness of human life). We selected textbooks used in teaching ethics at school from between 1935 and 1937, and those used in junior high schools today (2019) and analyzed what emotional and moral associations such contents generated. The analysis was performed with an automatic moral and emotional reasoning agent and based on the largest available text corpus in Japanese as well as on the resources of a Japanese digital library. As a result, we found out that, despite changes in stereotypical view on Japan’s moral sentiments, especially due to historical events, past and contemporary Japanese share a similar moral evaluation of certain basic moral concepts, although there is a large discrepancy between how they perceive some actions to be beneficial to the society as a whole while at the same time being inconclusive when it comes to assessing the same action’s outcome on the individual performing them and in terms of emotional consequences. Some ethical categories, assessed positively before the war, while being associated with a nationalistic trend in education have also disappeared from the scope of interest of post- war society. The findings of this study support suggestions proposed by others that the development of personal AI systems requires supplementation with moral reasoning. Moreover, the paper builds upon this idea and further suggests that AI systems need to be aware of ethics not as a constant, but as a function with a correction on historical and cultural changes in moral reasoning.     

The effects of self-brand connections on responses to brand failure: A new look at the consumer–brand relationship

We argue that consumers with high self-brand connections (SBC) respond to negative brand information as they do to personal failure — they experience a threat to their positive self-view. After viewing negative brand information, high (vs. low) SBC consumers reported lower state self-esteem. Consumers with high SBC also maintained favorable brand evaluations despite negative brand information. However, when they completed an unrelated self-affirmation task, they lowered their brand evaluations the same as low SBC consumers. This finding suggests that high SBC consumers' reluctance to lower brand evaluation might be driven by a motivation to protect the self rather than the brand.     

Automatic question generation and answer assessment for subjective examination

Automatic generation of questions and evaluating their answers is a highly challenging task in natural language processing and educational technology. This work focuses on generating subjective questions and also an evaluation system is suggested for assessing the answers. For generating the questionnaires, key-phrases are extracted from the course curriculum (syllabus). Next, based on the key-phrases, different types of subjective questions are generated. Finally, the evaluation of student’s responses is achieved using a multi-criteria-decision-making approach. It uses a set of model answers taken from different textbooks and subject experts to evaluate the answers. Multiple measures are used to assess the answers by comparing them with this model set. The results of the profound system reveal that the automated appraisal process can reduce the manual effort of the human.     

Mother-Infant Interaction Kinect Analysis (MIIKA): An automatic kinematic-based methodology for the investigation of interpersonal distance during early exchanges

Interpersonal distance is a core aspect of mother-child interaction. While conventional measures based on human coders do not fully capture the dynamics of this feature, computational methods provide automatic measures which can detect even small changes and more accurate estimates both spatially and temporally. Using RGB-D sensors (Microsoft Kinect V2), the present study describes a setup to automatically examine interpersonal distance during mother-child interactions, termed Mother-Infant Interaction Kinect Analysis (MIIKA). First, the laboratory setting and the data extraction method are described. By using an ad-hoc algorithm for kinematic data extraction, MIIKA returns three metrics: barycenter position (distance and velocity of approach and separation), movements (number of small, medium and large approaches and separations) and contributions (proportional contributions of mother and child to approaches and separations). Secondly, preliminary MIIKA metrics are described for a non-clinical mother-child dyad as an exemplification of the protocol. As interpersonal distance can be affected by contingent situations, we detected mother-infant full skeleton during three interactional contexts characterized by different kinds of dyadic exchanges: a free play session, a task-oriented activity and an emotionally arousing condition. Results highlighted similarities and differences between the three interactional contexts. MIIKA appears to be a promising setup to automatically examine interpersonal distance in early mother-child interactions.