Visual Analysis of Social Robots in Twitter on China Agenda Setting

With the development and progress of intelligent algorithms, more and more social robots are used to interfere with the information transmission and direction of international public opinion. This paper takes the agenda of COVID-19 in Twitter as the breakthrough point, and through the methods of web crawler, Twitter robot detection, data processing and analysis, aims at the agenda setting of social robots for China issues, that is, to carry out data visualization analysis for the stigmatized China image. Through case analysis, concrete and operable countermeasures for building the international communication system of China image were provided. © 2022 IEEE.

Lighting up well-being with Bulb

Due to the Covid-19 pandemic, two problems arose. Students lacked 1) social opportunities and 2) motivation to maintain their schedules, e.g., studying or relaxing, as their work-life balance disappeared. Thus, we designed a social companion robot, Bulb, that helped students cycle through daily activities with subtle cues, i.e., light, gaze, and movements. Bulb's "head"would light up with different colors or it gazes at different parts of the room, e.g., at the laptop to hint at studying or wiggling to suggest a small break. Five students evaluated Bulb through at-home use, which demonstrated that Bulb was seen as a "living being"and students were responsive to its social cues, like following Bulb's gaze, resulting in a higher awareness and follow-through of students' schedules. Our contribution is in designing a social companion robot that subtly persuaded students through light and anthropomorphic social cues, helping them maintain their daily schedule during the pandemic. © 2023 Owner/Author.

Scaling-Up Social Learning in Small Groups with Robot Supported Collaborative Learning (RSCL): Effects of Learners' Prior Experience in the Case Study of Planning Poker with the Robot NAO

The COVID-19 pandemic accelerated the shift to online learning in higher education, making the need to rethink pedagogical approaches to on-campus education stronger than ever before. While online learning offers a wide range of benefits for both teachers and students, social, face-to-face interaction provides a strong rationale for in-person education. This paper proposes a novel approach to enhancing in-person social learning experiences through robot-supported collaborative learning facilitated by a social robot NAO in the case study "Planning poker with NAO”, which is a collaborative game-based activity facilitated by the robot. The case study was designed to provide a scalable social learning experience in small groups of students. The evaluation results from a study with 46 university students who played Planning poker with NAO explore different quality aspects of the learning experience. The results indicate that students valued both the social learning experience and the robotic facilitator. The analysis revealed some significant differences among students with and without prior experience in interacting with NAO, suggesting directions for future research related to novelty and familiarisation effects as well as to scaling up of social learning in small groups by applying social robots. © 2023 by the author.

Tamagotchi on Our Couch: Are Social Robots Perceived as Pets?

Although social robots increasingly enter our lives, it is not clear how they are perceived. Previous research indicates that there is a tendency to anthropomorphize social robots, at least in the Western culture. One of the most promising roles of robots in our society is companionship. Pets also fulfill this role, which gives their owners health and wellbeing benefits. In our study, we investigated if social robots can implicitly and explicitly be perceived as pets. In an online experiment, we measured implicit associations between pets and robots using pictures of robots and devices, as well as attributes denoting pet and non-pet features, in a Go/No-Go Association Task (GNAT). Further, we asked our participants to explicitly evaluate to what extent they perceive robots as pets and if robots could replace a real pet. Our findings show that implicitly, but not explicitly, social robots are perceived as pets. © 2022 The authors and IOS Press. All rights reserved.

Tell Me About It: Adolescent Self-Disclosure with an Online Robot for Mental Health

Self-disclosure to a social robot is a mental health intervention that can decrease stress for adolescents. Online digital robots provide the potential to scale this intervention especially in COVID-19 social distancing situations. However, self-disclosure interactions with digital social robots remain relatively unexplored. We conducted two online self-disclosure studies with adolescents (13-19 years old): our Active Listening Study compared experiences sharing positive, negative, and neutral feelings with a social robot, while our Journaling Study explored differences in sharing stressors by speaking with and without a social robot and by writing. We found that positive prompt tone improved mood while neutral prompt decreased stress, and less negative attitudes toward robots correlate with more qualitatively positive experiences with robot interactions.We also found robot disclosure interactions hold promising potential as a preferred method of self-disclosure over solo speaking, moderated by negative attitudes toward robots. This paper outlines limitations and future work from these studies. © 2023 IEEE Computer Society. All rights reserved.

Holobot: Hologram based Extended Reality Telepresence Robot

Nowadays, telepresence systems based on the Extended Reality (XR) system are actively developed and used for remote collaboration due to COVID-19. Still, several issues, such as limited traversable space in Virtual Reality (VR) and require all participants to wear head-mounted display (HMD), stop these systems from being used in our daily life. On the other hand, telepresence robots have been used in various fields before the pandemic. However, these robots also have a limitation in that the current form is incapable of delivering non-verbal expressions, which is essential for social interaction. Therefore, we present a Holobot, a telepresence robot based on the XR system. A remote user connects to the Holobot through VR HMDs, and the Holobot augments a virtual avatar that projectsusers' facial and gesture expressions.We developed a prototype and conducted a simple field test in the exhibition to receive feedback. VR participants enjoyed exploring remote spaces and interacting with each other through Holobot. Furthermore, remote space participants mentioned that a 1:1 scale avatar helped to build co-presence with the VR user. Based on these insights, we think Holobot could provide design guideline for future telepresence robot. For further approach, we plan to improve our prototype and conduct user test for structured evaluation of our system. © 2023 IEEE Computer Society. All rights reserved.

A New Study of Integration Between Social Robotic Systems and the Metaverse for Dealing with Healthcare in the Post-COVID-19 Situations

With the popularity of the metaverse, researchers are turning to augmented reality and virtual reality to innovate their recent pain points, particularly healthcare issues during COVID-19. At the same time, social robots can be a great tool for alleviating many challenges during the pandemic. However, before the integrated technology's possibilities for the metaverse and social robots can be suitably harnessed, certain recent developments for integration during the pandemic should be addressed. For this reason, this paper proposes a new systematic summary of pioneering social robotic systems using the metaverse through immersive experiences from an interdisciplinary healthcare perspective during the COVID-19 outbreak. We also highlight social robots to deal with medical healthcare issues during the virus outbreak both elderly adults and younger people. Moreover, we compare recent metaverse-driven social robotic works for dealing with assisted living and healthcare issues through telepresence and remote interaction during COVID-19. Ultimately, we provide a recommendation and forecast a future scenario for the integration between socially interactive robots and metaverse technology to improve and help the quality of life both in the current COVID-19 situation and in the post-COVID-19 society. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Entrepreneurship innovation using social robots in tourism: a social listening study

The tourism sector has been one of the most impacted by the COVID-19 pandemic, due to restrictions on mobility and fear of social contact. In this context, business innovation through digital transformation is presented as a great opportunity for the tourism industry and the inclusion of social robots in service tasks is an example. This transformation requires new methodologies, skills and talent that must be promoted to improve the innovative tourism ecosystem. With this research, we try to determine how the inclusion of social or service robots in hotels can improve the image and perception held by clients or guests. For that, we first analyse the degree of knowledge and sentiment generated by social robots through a social listening study in social networks. In addition, we determine whether these perceptions on the subject are in tune with other more formal fields, such as scientific research, or with the strategies followed at a national or international level by companies, agencies and organisations related to the technology and innovation of social robotics. For both objectives, we use the Simbiu social listening tool, a software-based program on Talkwalker, and we obtain interesting results. Basically, people on Twitter have a neutral or positive feeling about the use of social robots, and people who write in English have a more positive attitude towards social robots than Spanish speakers. After COVID-19, are necessary changes in strategic decisions of the hospitality and it is essential to continue investigating the role of social robots in this new context. © 2023, The Author(s).

Addressing loneliness in the workplace through human-robot interaction: Development and evaluation of a social office robot concept

New work has been a topic for a few years now and the COVID-19 pandemic has brought this trend more into focus, i.e., working remotely became more popular. However, besides various advantages, there is the risk of loneliness in employees, which can negatively affect their work performance and mental health. Research in different domains suggests that social robots could reduce loneliness. Since we were interested in whether and how such findings are transferable to the office context, we developed and tested a concept for a social office robot. More specifically, we first conducted a cultural probes study with white-collar workers to gain information about workplace loneliness and its drivers. Second, we explored design possibilities for a social office robot in a focus group. Based on the results, we created a concrete concept, Luca, which we finally evaluated and optimized with the help of interviews with participants from various industries. The present work contributes to HRI research and practice, e.g., by providing design recommendations for the implementation of a social office robot. Future research could investigate the effectiveness of a social office robot intervention in field studies. Next to implications for research and practice, potential limitations are discussed. © 2023 the author(s), published by De Gruyter, Berlin/Boston 2023.

Buzzo or Eureka - Robot that Makes Remote Participants Feel More Presence in Hybrid Discussions

Teleconferencing technology has been widely used in the context of the covid-19 pandemic. However, local and remote participants always have a poorer experience of hybrid discussion for various reasons in the leaderless group discussions with mixed online and offline members. In this paper, this phenomenon is explored through an early pilot study. We found problems with the lack of presence of remote participants in hybrid discussion sessions, as well as unclear information about the status of members. To solve such problems, we've designed a social robot called SNOTBOX. The bot indicates the participation status (marginalized or not) of the remote participant using "Buzzo" and the remote participant's desire to be heard through a "Eureka". We used both representations to attract the attention of local participants as a way to enhance the presence of remote participants in the conference. SNOTBOX is easy to produce and allows for DIY customization, and also supports multi-participant online discussions. © 2023 IEEE Computer Society. All rights reserved.

Loneliness During COVID-19 Influences Mind and Likeability Ratings in the Uncanny Valley

To combat the spread of the COVID-19 virus, countries enforced quarantines, physical and social restrictions on people. These restrictions left many feeling isolated and lonely due to prolonged quarantines and lockdowns. This raises questions about using robots as social support to alleviate these symptoms, while still complying with restrictions and regulations. Since acceptance of social robots as companions has traditionally been low, an event like COVID-19 could change acceptance of robots as social companions as loneliness can influence the likelihood of anthropomorphizing nonhuman agents. Here, we aimed to see if loneliness, due to COVID-19 restrictions, influence the Uncanny Valley pattern that prior work has shown. As such, participants saw robot images that varied in physical human-likeness and were asked to evaluate them regarding trustworthiness, mind perception and likability. The measurements were obtained once before COVID-19 (in 2016) and once at the peak of the pandemic in September 2020. Results show that ratings of mind perception and likability were significantly impacted by the pandemic, with less pronounced UV patterns for those who experienced the COVID-19 pandemic. However, no differences in the UV pattern was observed on trust. Post-hoc analyses also illustrated that people were more likely to judge machinelike robots negatively, which could be due to increased loneliness/anxiety. These data suggest that loneliness attenuates UV patterns that are observed in "Uncanny” robots and that people have more favorable attitudes towards humanlike robots when feeling lonely, which provides important considerations for the use of humanlike robots as social companions. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Barriers and Facilitators of Robot-Assisted Education in Higher Education: A Systematic Mixed-Studies Review

Lack of motivation and enjoyment is a challenge that many students face. Due to the current coronavirus pandemic, many lessons are not being conducted face-to-face. However, the use of robots has been proven able to alleviate this challenge. This review explores the barriers and facilitators of robot-assisted education among higher education students. Ten databases were comprehensively searched for studies in English. Both published and unpublished studies were considered without a time limit. A systematic mixed-studies review was adopted and the mixed method appraisal tool was used to assess the methodological quality of the selected articles. The qualitative and quantitative findings were then synthesized via thematic and narrative syntheses, respectively. To integrate these two sets of findings, a result-based convergent synthesis was performed. A total of 28 studies covering 1689 higher education students across 14 countries were eventually used for the analysis. Most of these studies had average to high methodological quality. Two barrier themes were identified from these studies, namely, poor audio verbatim from the robots, and disruption and restrictions from software and hardware of the robot. Meanwhile, three themes related to facilitators were identified, namely, greater engagement in learning, facilitation in remote learning, and knowledge enhancement. The use of robot-assisted education has been proven to improve student learning in higher education. Robot-assisted education is an alternate educational technique that can be utilized to supplement and augment ongoing teaching arrangements. Future studies should examine a specific type of robot in a comparable learning environment.

Supporting Remote Social Robot Design Collaboration with Online Canvases: Lessons Learned from Facilitators' and Participants' Experiences.

Social robot design projects typically involve multidisciplinary teamwork and collaboration, adopt a Human-Centred Design (HCD) approach, and deal with physical (tangible) objects, i.e., robots. HCD takes a human to the centre point of the design process. A typical activity in HCD are design workshops where a facilitator is needed to guide and moderate the task-related and interactional activities throughout the session. Facilitation is also usually needed in longer-term design projects or courses to guide participants through the different phases of design during several sessions. Recently, due to the COVID-19 pandemic, most design activities including social robot design were rapidly transferred to online mode. Designing for tangible objects is challenging in online settings because the interaction experience with a physical object is hard to demonstrate online. In this article, we report how we harnessed online canvases to support both short-term social robot design workshops and a long-term design course. Based on participants' feedback and facilitators' experiences, we report lessons learned from utilizing collaborative design canvases for creative social robot design projects that specifically focus on early stages and concept ideation. We propose practical guidelines for canvas-based online facilitation focusing on creative design workshops and projects. In addition, we discuss the lessons learned concerning social robot design activities taking place in online mode. To respond to the challenges of designing tangible robots in a fully online mode, we suggest a Hybrid Robotic Design Model (HRDM), where the participants work in contact with facilitators, other participants and robots at specific points, while the other phases are conducted online.

User experience of human-robot long-term interactions

Since interactions with social robots are novel and exciting for many people, one particular concern in this specific area of human-robot interaction (HRI) is the extent to which human users will experience the interactions positively over time, when the robot's novelty is particularly salient. In the current paper, we investigated users' experience in long-term HRIs;how users perceive the ongoing interactions and the robot's ability to sustain it over time. Therefore, here we examine the effect of the repeated measures (10 testing sessions) and the discussion theme (Covid-19 related vs general) on the way participants experienced the interaction quality with a social robot and perceived the robot's communication competency over time. We found that despite individual differences between the participants, over time participants found the interactions with Pepper to be of higher quality and that Pepper's communication skills got better. Nevertheless, our results also stressed that the discussion theme has no meaningful nor significant effect on the way people perceive Pepper and the interaction. © 2022 ACM.

Towards a Humanoid Teaching Assistant-Robot-Primitives Knowledge Modeling

Education is defined as the process of building an individual and eradicating illiteracy from society. Education is the main engine of the prosperity and development of civilizations. In addition, to being the center of measurement of growth and development of societies, all peoples care about it and seek to develop it. Given the difficult conditions that the world is going through due to the epidemic of Covid-19, the educational sector has a renewed interest in a humanoid social robot, to limit contact with the public and avoid overcrowding in schools and keep pace with education despite the pandemic. This paper aims to propose an interactive tutoring environment, using an assisting humanoid robot to support the teaching and learning process in the classroom. Statistics indicate that the use of educational robots has seen a notable evolution recently, more than 85.70% of teachers have been using robots in the classroom for less than 5 years. The teaching humanoid robot assistant can catch student’s attention, then help teachers improve the way they present their courses and manage their classes. In this work, we represent the main activities that a teacher does to invade the classroom to have a good session with his students. All these activities represent knowledge level tasks for the teacher, while for our humanoid robot assistant, we have defined its tasks that represent primitive level tasks, and we have chained these tasks to give a generic knowledge model that allows defining a knowledge level task for the teacher from a composition of primitives tasks of the assistant humanoid robot in the teaching act. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

IRRMA: An Image Recommender Robot Meeting Assistant

The number of people who attend virtual meetings has increased as a result of COVID-19. In this paper, we present a system that consists of an expressive humanoid social robot called QTRobot, and a recommender system that employs natural language processing techniques to recommend images related to the content of the presenter’s speech to the audience in real time. This is achieved utilising the QTRobot’s platform capabilities (microphone, computation power, and Wi-Fi). © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Human-Robot Co-Teaching in Online University Course during Covid-19

Online lectures are extensively used in the academic area. Especially due to the Covid-19 lockdown restriction measures, the educational institutions were forced to conduct online classes. Consequently, it is important to determine how these classes can become more enjoyable while at the same time delivering the academic objectives to the students and how academic tutors can optimally interact with students. This paper specifically looks at the performance of social robots in place of university co-tutors, in the field of engineering, measuring the students' enjoyment and understanding of the basic principles of the lecture's content. Inspired by previous educational studies which have evidenced beneficial effects for both students and tutors after taught/conducting lectures with two collaborative tutors, the goal of this research is a) to test the students' evaluation of two collaborative human tutors in comparison with one individual human when teaching academic lectures during online lectures, and b) to investigate the effect of a social robot co-tutor after comparing students understanding and level of enjoyment after attending a lecture given by human-human or human-robot co-tutors. The lectures took place via an online educational platform during an actual university course. Results indicated that students evaluated higher the co-tutor lectures in comparison with the individual tutor lectures, while they equally enjoyed and gained knowledge from both human-human and human-robot cotutored lectures. © 2022 IEEE.

Mental Health Problems of Older Adults During the COVID-19 Pandemic: Effects, Recommendations and Healthcare Robot-Mediated Therapy

The outbreak of the coronavirus pandemic in 2019, declared as a major public health emergency, profoundly affected the mental health of older adults. Several studies have provided reasonable recommendations to alleviate these effects. A vital role was played by healthcare robots in providing the psychosocial care to the older adults. This review analyzes relevant studies and addresses the research progress on the effects, recommendations, and robot-mediated therapy to alleviate mental health problems developed among older adults during the pandemic. Social robots can provide strong support for mental health. © 2022 IEEE.

Methodologies Used to Study the Feasibility, Usability, Efficacy, and Effectiveness of Social Robots For Elderly Adults: Scoping Review.

BACKGROUND: New research fields to design social robots for older people are emerging. By providing support with communication and social interaction, these robots aim to increase quality of life. Because of the decline in functioning due to cognitive impairment in older people, social robots are regarded as promising, especially for people with dementia. Although study outcomes are hopeful, the quality of studies on the effectiveness of social robots for the elderly is still low due to many methodological limitations. OBJECTIVE: We aimed to review the methodologies used thus far in studies evaluating the feasibility, usability, efficacy, and effectiveness of social robots in clinical and social settings for elderly people, including persons with dementia. METHODS: Dedicated search strings were developed. Searches in MEDLINE (PubMed), Web of Science, PsycInfo, and CINAHL were performed on August 13, 2020. RESULTS: In the 33 included papers, 23 different social robots were investigated for their feasibility, usability, efficacy, and effectiveness. A total of 8 (24.2%) studies included elderly persons in the community, 9 (27.3%) included long-term care facility residents, and 16 (48.5%) included people with dementia. Most of the studies had a single aim, of which 7 (21.2%) focused on efficacy and 7 (21.2%) focused on effectiveness. Moreover, forms of randomized controlled trials were the most applied designs. Feasibility and usability were often studied together in mixed methods or experimental designs and were most often studied in individual interventions. Feasibility was often assessed with the Unified Theory of the Acceptance and Use of Technology model. Efficacy and effectiveness studies used a range of psychosocial and cognitive outcome measures. However, the included studies failed to find significant improvements in quality of life, depression, and cognition. CONCLUSIONS: This study identified several shortcomings in methodologies used to evaluate social robots, resulting in ambivalent study findings. To improve the quality of these types of studies, efficacy/effectiveness studies will benefit from appropriate randomized controlled trial designs with large sample sizes and individual intervention sessions. Experimental designs might work best for feasibility and usability studies. For each of the 3 goals (efficacy/effectiveness, feasibility, and usability) we also recommend a mixed method of data collection. Multiple interaction sessions running for at least 1 month might aid researchers in drawing significant results and prove the real long-term impact of social robots.