The MatchNMingle dataset A novel multi-sensor resource for the analysis of social interactions and group dynamics in-the-wild during free-standing conversations and speed dates

Objectives: This study proposes an alternative hypothetical scenario method capitalizing on the potential of virtual reality (VR). Rather than asking participants to imagine themselves in a specific situation, VR perceptually immerses them in it. We hypothesized that experiencing a scenario in VR would increase feelings of being "present" in the situation, and add to perceived realism compared to the written equivalent. This, in turn, was

In a rapidly digitizing world, machine learning algorithms are increasingly employed in scenarios that directly impact humans. This also is seen in job candidate screening. Data-driven candidate assessment is gaining interest, due to high scalability and more systematic assessment mechanisms. However, it will only be truly accepted and trusted if explainability and transparency can be guaranteed. The current chapter emerged from ongoing discussions between psychologists and computer scientists with machine learning interests, and discusses the job candidate screening problem from an interdisciplinary viewpoint. After introducing the general problem, we present a tutorial on common important methodological focus points in psychological and machine learning research. Following this, we both contrast and combine psychological and machine learning approaches, and present a use case example of a data-driven job candidate assessment system, intended to be explainable towards non-technical hiring specialists. In connection to this, we also give an overview of more traditional job candidate assessment approaches, and discuss considerations for optimizing the acceptability of technology-supported hiring solutions by relevant stakeholders. Finally, we present several recommendations on how interdisciplinary collaboration on the topic may be fostered.

Objectives. This article explores the potential of virtual reality to study burglary by measuring user responses on the subjective, physiological and behavioral levels. Furthermore, it examines the influence of individual dispositions, such as sensation seeking and self-control, on behavior during a virtual burglary event. Methods. Participants, male university undergraduates (N=77), could freely move around a virtual neighborhood wearing a virtual reality headset and using a game controller, and were instructed to burgle one of the houses in the neighborhood. Participant movement, items stolen from the house, and heart rate were recorded throughout the burglary event. Individual dispositions were measured before, and subjective user responses were measured after, the event. Additionally, we experimentally varied whether there was an alarm sounding, and participants' beliefs about the chance of getting caught (deterrence). Results. Participants reacted subjectively to the burglary event by reporting high levels of presence in the virtual environment and physiologically by showing increased heart rates. In terms of behavior, high deterrence resulted in fewer items being stolen and a shorter burglary. Furthermore, sensation seekers stole more valuable items, while participants high in conscientiousness stole fewer items. Conclusions. The results suggest that virtual environments have substantial potential for studying criminal behavior. 2 Watching burglars in action would be an excellent way to increase our knowledge of burglary. In practice this is only rarely possible, however, and even less so in a controlled setting that allows for systematic study. By virtue of its illegal nature, burglary, analogous to other serious offenses, occurs out of sight and hence is hard to observe and examine 'in the wild'. Even in those cases that would allow for direct observation, ethical considerations generally militate against it. Consequently, our knowledge of burglary relies in large part either on studies examining targeting patterns and target characteristics, or on studies using retrospective methods, such as offender interviews and surveys. The former type of research has yielded crucial insights on areas where burglaries are likely to take place (e.g., Johnson and Bowers, 2004; Townsley, Homel and Chaseling, 2003) and offending trajectories taken (e.g., Bernasco, 2010), but offers little in the way of burglar decision-making processes while committing the offense (Coupe, in press; Wright and Decker, 1994). Interview studies have provided valuable insights into offender decision-making (e.g.,

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