Large Language Model (LLM)-powered web GUI agents are increasingly automating everyday online tasks. Despite their popularity, little is known about how users’ preferences and values impact agents’ reasoning and behavior. In this work, we investigate how both explicit and implicit user preferences, as well as the underlying user values, influence agent decision-making and action trajectories. We built a controlled testbed of 14 common interactive web tasks, spanning shopping, travel, dining, and housing, each replicated from real websites and integrated with a low-fidelity LLM-based recommender system. We injected 12 human preferences and values as personas into four state-of-the-art agents and systematically analyzed their task behaviors. Our results show that preference and value-infused prompts consistently guided agents toward outcomes that reflected these preferences and values. While the absence of user preference or value guidance led agents to exhibit a strong efficiency bias and employ shortest-path strategies, their presence steered agents’ behavior trajectories through the greater use of corresponding filters and interactive web features. Despite their influence, dominant interface cues, such as discounts and advertisements, frequently overrode these effects, shortening the agents’ action trajectories and inducing rationalizations that masked rather than reflected value-consistent reasoning. The contributions of this paper are twofold: (1) an open-source testbed for studying the influence of values in agent behaviors, and (2) an empirical investigation of how user preferences and values shape web agent behaviors.

As more people meet, interact, and socialize online, Social Virtual Reality (VR) emerges as a technology that bridges the gap between traditional face-to-face and online communication. Unlike traditional screen-based applications, Social VR provides immersive, spatial, and three-dimensional social interactions, making it a potential tool for enhancing remote collaborations. Despite the growing interest in Social VR, research on its role in collaboration remains fragmented, calling for a synthesis to identify research gaps and future directions. We conducted a 20-year scoping review, screening 2,035 articles and identifying 62 articles that addressed how Social VR has supported collaboration. Our analysis shows three key levels of support: Social VR can enhance individual perceptions and experiences within their groups, foster team dynamics with virtual elements that enable realistic interactions, and employ the unique affordances of VR to augment users’ spaces. We discuss how future research in Social VR should move beyond replicating physical-world interactions and explore how immersive environments can cultivate long-term collaboration, trust, and more diverse and inclusive participation. This review highlights the current practices and challenges, highlighting new opportunities for theorizing and designing Social VR systems that responsibly support remote collaborations.

Team closeness provides the foundations of trust and communication, contributing to teams' success and viability. However, newcomers often struggle to be included in a team since incumbents tend to interact more with other existing members. Previous research suggests that online communication technologies can help team inclusion by mitigating members' perceived differences. In this study, we test how virtual reality (VR) can promote team closeness when forming teams. We conducted a between-subject experiment with teams working in-person and VR, where two members interacted first, and then a third member was added later to conduct a hidden-profile task. Participants evaluated how close they felt with their teammates after the task was completed. Our results show that VR newcomers felt closer to the incumbents than in-person newcomers. However, incumbents' closeness to newcomers did not vary across conditions. We discuss the implications of these findings and offer suggestions for how VR can promote inclusion.

Although domestic work is often viewed as manual labor, it involves significant interaction with online technologies. However, the detailed exploration of how domestic workers use these technologies remains limited. This study examines the impact of online technologies on domestic workers' work practices, perceptions, and relationships with customers and employers. We interviewed 30 domestic workers residing in the United States, who provided examples that highlight the insufficient transformative role of current online technologies in their work. By conducting a thematic analysis, we characterize how they approach and avoid these digital tools at different stages of their work. Through these findings, we investigate the limitations of technology and identify challenges and opportunities that could inform the design of more suitable tools to improve the conditions of this marginalized group.

Although knowledge workers are increasingly able to adopt remote and hybrid working arrangements and work productively, many organizations continue to question the effectiveness of remote work and focus on its concerns and challenges. Previous CSCW research shows that remote workers have limited awareness of other workers, require more explicit coordination, and feel excluded from in-person colleagues. Research also shows that adopting work practices and technologies that are remote work-friendly can offset many of these challenges. Identifying which effective practices and challenges are most helpful or hurtful to remote workers-and how workplace attributes (e.g., team structure; communication frequency; tool use) affect them-could strengthen organizations' strategies and policies for remote work. Through a theoretically-informed survey of 1,526 U.S. knowledge workers, we find many factors prior research has argued as essential to remote work, such as knowing your teammates personally, to be the least important for remote workers, and show how workplace attributes influence those perceptions. We provide theoretical and practical implications for future research for organizations that wish to support remote and hybrid work modalities.

In the past decade, HCI researchers have developed virtual reality (VR), augmented reality (AR), and mixed reality (MR) solutions to support fashion designers. Unlike traditional technologies, VR/AR/MR technologies provide immersion and physical interactions with digital garments. To comprehend the transformative impact of these technologies in fashion design, we conducted a systematic review covering 2013 to 2023, assessing the impact of VR/AR/MR adoption in fashion design. After screening 126 articles, we identified 26 articles that introduce immersive systems centered on two main themes: advancing the fashion design toolkit and enhancing fashion design processes. We discuss potential opportunities and limitations to be studied in future research and reflect on how VR/AR/MR technologies can continue to support fashion designers in fulfilling their needs and overcoming obstacles.

In this paper, we analyze the factors that are most likely to explain the formation of friendship and advice ties among 44 students from a professional STEM graduate program. To answer our research questions, we investigate how students' characteristics influence the formation of their friendship and advice networks using descriptive network analysis, community detection, and Exponential Random Graph Models. The results show that the formation of friendship and advice ties is mostly driven by demographic homophily and prior group activities. Our findings also suggest that female students were more constrained in their friendship and advice networks than male students. We discuss the implications of these results for how graduate students' social networks form at the beginning of their program.

Despite the benefits of team diversity, individuals often choose to work with similar others. Online team formation systems have the potential to help people assemble diverse teams. Systems can connect people to collaborators outside their networks, and features can quantify and raise the salience of diversity to users as they search for prospective teammates. But if we build a feature indicating diversity into the tool, how will people react to it? Two experiments manipulating the presence or absence of a "diversity score" feature within a teammate recommender demonstrate that, when present, individuals avoid collaborators who would increase team diversity in favor of those who lower team diversity. These results have important practical implications. Though the increased access to diverse teammates provided by recommender systems may benefit diversity, designers are cautioned against creating features that raise the salience of diversity as this information may undermine diversity.

The emergence of team-assembly technologies has brought with it new challenges in designing and implementing socio-technical systems. Our understanding of how systems shape the team-assembly processes is still limited. How do systems enable users to find teammates? How do users make decisions when using these systems? And what factors explain the characteristics of the teams assembled? Building on existing literature from CSCW, computer science, and management science, we propose a taxonomy to characterize how systems influence team assembly. This taxonomy argues that two dimensions determine how systems shape team assembly: (i) users? agency, to what extent the system enables its users to exercise their agency, and (ii) users? participation, how many users the system allows to participate in the team-formation process. The intersection of these two dimensions manifest four types of teams enabled by systems: self-assembled teams, staffed teams, optimized teams, and augmented teams. We characterize each one of these types of teams, considering their qualities, advantages, and challenges. To contextualize these types of teams, we map the current literature of team-assembly systems using a scoping literature review. Lastly, we discuss ways through which these two dimensions alter users' behavior, team diversity, and team composition. This paper provides theoretical implications and research questions for future systems that reconfigure the organization of people into teams.

People and organizations are increasingly using online platforms to assemble teams. In response, HCI researchers have theorized frameworks and created systems to support team assembly. However, little is known about how users search for and choose teammates on these platforms. We conducted a field study where 530 participants used a team formation system to assemble project teams. We describe how users' traits and social networks influence their teammate searches, teammate choices, and team composition. Our results show that (a) what users initially search for differs from what they finally choose: initially they search for experts and sociable users, but they are ultimately more likely to choose their prior social connections as their teammates; (b) users' decisions lead to non-diverse and segregated teams, where most of the expertise and social capital are concentrated in a few teams. We discuss the implications of these results for designing team formation systems than promote users' agency.

The field of Computer Supported Cooperative Work (CSCW) has an enduring interest in studying and designing technologies that bring people together in partnerships, teams, crowds, communities, and other collectives. As the technologies enabling group formation have evolved, so too have the guiding questions pursued by CSCW scholars. This review outlines the trajectory of scholarship on group formation with an eye towards the most pressing future questions in this area. To understand how CSCW researchers have studied technology-enabled group formation, we systematically review articles published at CSCW from 1992 to 2018. Exploring more than 2,000 potentially relevant works, we identified 35 focused on technologies and group formation. Content coding and thematic analysis revealed four periods and six themes in the study of online group formation. These themes include: group composition, self-presentation, assembly mechanisms, recruitment, organizing structures, and group culture. Quo vadis? Based on our review, we offer recommendations for the next generation of CSCW scholarship seeking to understand and enable collectives joining together online.

News articles often use narrative frames to present people, organizations, and facts. These narrative frames follow cultural archetypes, enabling readers to associate each of the presented elements with familiar stereotypes, well-known characters, and recognizable outcomes. In this way, authors can cast real people or organizations as heroes, villains, or victims. We present a system that identifies the main entities of a news article, and determines which is being cast as a hero, a villain, or a victim. As currently implemented, this system interacts directly with news consumers through a browser extension. Our hope is that by informing readers when an entity is cast in one of these roles, we can make implicit bias explicit, and thereby assist readers in applying their media literacy skills. This approach can also be used to identify roles in well-understood event sequences in a more prosaic manner, e.g., for information extraction.