The platforms that host online gaming groups and communities continue to evolve, and it has become possible to join, participate in, and consume content from groups that exist across multiple tools, platforms, and spaces at the same time. In this paper, we explore how groups use and rely upon assemblages of multiple online spaces to accomplish the "work" of participating in these gaming groups. We present an interview study with users of the100.io, a platform that hosts gaming community spaces, helps players find groups, and operates as a gaming event scheduling tool for its users. Contrary to our initial assumptions, we found that users relied upon the100 as a kind of glue for flexibly-interconnected, multi-space group configurations. These multi-space groups support our participants' desires to approach online gaming as a social practice, provide additional accountability among players, and enable multiple forms of social participation within those communities. Our findings point towards opportunities to expand social computing scholarship to better describe how users of online communities flexibly bridge across technical infrastructure.

Real-time mental stress monitoring from surgeons and surgical staff in operating rooms may reduce surgical injuries, improve performance and quality of medical care, and accelerate implementation of stress-management strategies. Motivated by the increase in usage of objective and subjective metrics for cognitive monitoring and by the gap in reviews of experimental design setups and data analytics, a systematic review of 71 studies on mental stress and workload measurement in surgical settings, published in 2001-2020, is presented. Almost 61% of selected papers used both objective and subjective measures, followed by 25% that only administered subjective tools - mostly consisting of validated instruments and customized surveys. An overall increase in the total number of publications on intraoperative stress assessment was observed from mid-2010 s along with a momentum in the use of both subjective and real-time objective measures. Cardiac activity, including heart-rate variability metrics, stress hormones, and eye-tracking metrics were the most frequently and electroencephalography (EEG) was the least frequently used objective measures. Around 40% of selected papers collected at least two objective measures, 41% used wearable devices, 23% performed synchronization and annotation, and 76% conducted baseline or multi-point data acquisition. Furthermore, 93% used a variety of statistical techniques, 14% applied regression models, and only one study released a public, anonymized dataset. This review of data modalities, experimental setups, and analysis techniques for intraoperative stress monitoring highlights the initiatives of surgical data science and motivates research on computational techniques for mental and surgical skills assessment and cognition-guided surgery.

External Human-Machine Interfaces (eHMI) are widely used on robots and autonomous vehicles to convey the machine’s intent to humans. Delivery robots are getting common, and they share the sidewalk along with the pedestrians. Current research has explored the design of eHMI and its effectiveness for social robots and autonomous vehicles, but the use of eHMIs on delivery robots still remains unexplored. There is a knowledge gap on the effective use of eHMIs on delivery robots for indicating the robot’s navigational intent to the pedestrians. An online survey with 152 participants was conducted to investigate the comprehensibility of the display and light-based eHMIs that convey the delivery robot’s navigational intent under common navigation scenarios. Results show that display is preferred over lights in conveying the intent. The preferred type of content to be displayed varies according to the scenarios. Additionally, light is preferred as an auxiliary eHMI to present redundant information. The findings of this study can contribute to the development of future designs of eHMI on delivery robots.

While research on human-robot interaction is ongoing as robots become more readily available and easier to use, the study of interactions between a human and a team of multiple robots represents a relatively new field of research. In particular, how multi-robots could be used for everyday users and how the characteristics of multi-robots would affect human perception and cognition has not been explored. In this paper, we specifically focus on physical affordances generated by the movements of multi-robots, and investigate the effects of deictic movements of multi-robots on information retrieval by conducting a delayed free recall task. We conclude with further discussion of how the movements of the multi-robot reshape the way of people perceiving information and what should be considered to design a multi-robot-based display.

Design practitioners are increasingly engaged in describing ethical complexity in their everyday work, exemplified by concepts such as "dark patterns" and "dark UX." In parallel, researchers have shown how interactions and discourses in online communities allow access to the various dimensions of design complexity in practice. In this paper, we conducted a content analysis of the subreddit "/r/assholedesign," identifying how users on Reddit engage in conversation about ethical concerns. We identify what types of artifacts are shared, and the salient ethical concerns that community members link with "asshole" behaviors. Based on our analysis, we propose properties that describe "asshole designers," both distinct and in relation to dark patterns, and point towards an anthropomorphization of ethics that foregrounds the inscription of designer's values into designed outcomes. We conclude with opportunities for further engagement with ethical complexity in online and offline contexts, stimulating ethics-focused conversations among social media users and design practitioners.

This paper introduces a new ROSbag-based multimodal affective dataset for emotional and cognitive states generated using the Robot Operating System (ROS). We utilized images and sounds from the International Affective Pictures System (IAPS) and the International Affective Digitized Sounds (IADS) to stimulate targeted emotions (happiness, sadness, anger, fear, surprise, disgust, and neutral), and a dual N-back game to stimulate different levels of cognitive workload. 30 human subjects participated in the user study; their physiological data were collected using the latest commercial wearable sensors, behavioral data were collected using hardware devices such as cameras, and subjective assessments were carried out through questionnaires. All data were stored in single ROSbag files rather than in conventional Comma-Separated Values (CSV) files. This not only ensures synchronization of signals and videos in a data set, but also allows researchers to easily analyze and verify their algorithms by connecting directly to this dataset through ROS. The generated affective dataset consists of 1,602 ROSbag files, and the size of the dataset is about 787GB. The dataset is made publicly available. We expect that our dataset can be a great resource for many researchers in the fields of affective computing, Human-Computer Interaction (HCI), and Human-Robot Interaction (HRI).

We present a new multi-robot system as a means of creating a visual communication cue that can add dynamic illustration to static figures or diagrams to enhance the power of delivery and improve an audience's attention. The proposed idea is that when a presenter/speaker writes something such as a shape or letter on a whiteboard table, multiple mobile robots trace the shape or letter while dynamically expressing it. The dynamic movement of multi-robots will further stimulate the cognitive perception of the audience with handwriting, positively affecting the comprehension of content. To do this, we apply image processing algorithms to extract feature points from a handwritten shape or letter while a task allocation algorithm deploys multi-robots on the feature points to highlight the shape or letter. We present preliminary experiment results that verify the proposed system with various characters and letters such as the English alphabet.

The rise of co-working and co-living spaces, as well as related shared spaces such as makerspaces and hackerspaces-a group we refer to as various types of "co-spaces" - has helped facilitate a parallel expansion of the "digital nomad (DN)" lifestyle. Digital nomads, colloquially, are those individuals that leverage digital infrastructures and sociotechnical systems to live location-independent lives. In this paper, we use Oldenburg's framework of a first (home), second (work), and third (social) place as an analytical lens to investigate how digital nomads understand the affordance of these different types of spaces. We present an analysis of posts and comments on the '/r/digitalnomad' subreddit, a vibrant online community where DNs ask questions and share advice about the different types of places and amenities that are necessary to pursue their digital nomad lifestyle. We found that places are often assessed positively or negatively relative to one primary characteristic: either they provide a means for nomads to maintain a clear separation between the social and professional aspects of their lives, or they provide a means to merge these aspects together. Digital nomads that favor the first type of place tend to focus on searching for factors that they feel will promote their own work productivity, whereas DNs that favor the second type of place tend to focus on factors that they feel will allow them to balance their work and social lives. We also build on linkages between the notion of a third place and the more recent theoretical construct of social infrastructure. Ultimately, we demonstrate how DNs' interests in co-spaces provide a kind of edge-case for CSCW and HCI scholars to explore how sociotechnical systems, such as variants of co-spaces, inform one another as well as signify important details regarding new ways of living and engaging with technology.