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Interest in hybrid collaboration and meetings (HCM), where several co-located participants engage in coordinated work with remote participants, is gaining unprecedented momentum after the rapid shift in working from home due to the COVID-19 pandemic. However, while the interest is new, researchers have been exploring HCM phenomena for decades, albeit dispersed across diverse research traditions, using different terms, definitions, and frameworks. In this article, we present a systematic literature review of the contexts and tools of HCM in the ACM Digital Library. We obtained approximately 1,200 results, which were narrowed down to 62 key articles. We report on the terms, citations, venues, authors, domains, study types, and data of these publications and present a taxonomic overview based on their reported hybrid settings' actual characteristics. We discuss why the SLR resulted in a relatively small number of publications, and then as a corollary, discuss how some excluded high-profile publications flesh out the SLR findings to provide important additional concepts. The SLR itself covers the ACM until November 2019, so our discussion also includes relevant 2020 and 2021 publications. The end result is a baseline that researchers and designers can use in shaping the post-COVID-19 future of HCM systems.

We present Domino, a descriptive framework for hybrid collaboration and hybrid coupling styles in partially distributed teams. Domino enables researchers to describe, analyze, and understand real-world hybrid collaboration practices, i.e., collaborative practices that involve simultaneous co-located and remote collaboration with phases of both synchronous and asynchronous work that spans multiple groupware applications and devices. It also helps to categorize collaborative activities based on yet undocumented hybrid coupling styles between the members of multiple partially distributed or co-located subgroups. Our Domino framework was derived from initial observations of real-world practice and refined by the detailed analysis of participants' behavior and working styles during a simulation of a complex hybrid collaboration task with six partially distributed teams of four users in our lab. The resulting framework allows researchers to view collaboration through a new analytical lens, use new analytical tools, and also derive implications for the design of collaborative tools.

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Personalization, aiming at supporting users individually, according to their individual needs and prerequisites, has been discussed in a number of domains including learning, search, or information retrieval. In the field of human–computer interaction, personalization also bears high potential as users might exhibit varying and strongly individual preferences and abilities related to interaction. For instance, there is a good amount of work on personalized or adaptive user interfaces (also under the notion of intelligent user interfaces). Personalized human–computer interaction, however, does not only subsume approaches to support the individual user, it also bears high potential if applied to collaborative settings, for example, through supporting the individuals in a group as well as the group itself (considering all of its special dynamics). In collaborative settings (remote or co-located), there generally is a number of additional challenges related to human-to-human collaboration in a group, such as group communication, awareness or territoriality, device or software tool selection, or selection of collaborators. Personalized Collaborative Systems thus attempt to tackle many of these challenges. For instance, there are collaborative systems that recommend tools, content, or team constellations. Such systems have been suggested in different domains and different collaborative settings and contexts. In most cases, these systems explicitly focus on a certain aspect of personalized collaboration support (such as team composition). This article provides a broader, concise overview of existing approaches to Personalized Collaborative Systems based on a systematic literature review considering the ACM Digital Library.