# A Survey on Multi-User Conversational Interfaces
## 2. Scope and Methodology  
As a starting point for our survey, we performed an initial search regarding MUCIs. The results revealed that the topic is highly relevant and that there exists considerable literature on the subject. However, it became clear that there is little correlation between the papers, and a cohesive research community could not be identified. The aim of this paper is therefore to give an overview of the research conducted on MUCIs by first providing a  
Figure 1. Traditional pipeline architecture of a conversational interface. Figure 2. Modular architecture of Multi-User Conversational Interfaces and their components. common definition of the term, then examining the methods and approaches used, and finally a comparison of key findings and guidelines for future systems. We conducted our literature review according to the PRISMA standards for systematic analysis [1]. For this, the publisher-independent global citation database 'Web of Science' (WoS) was used as a digital library. We chose WoS as our primary database since it is widely recognised for its strong indexing standards and comprehensive coverage of high-impact journals and conferences in computer science and engineering (including more than 34,865 journals, books, proceedings, patents, and datasets). Although no single database can claim exhaustive coverage, WoS offers several advantages: it ensures a baseline of quality by enabling manual adjustments of inclusion criteria, provides reliable citation data for impact analysis, and is frequently used in systematic reviews to identify research trends. Additional significant publications known to the authors were also included. After identifying keywords through a pilot search, we were able to determine a search string which is shown in Table 1. Our survey considers all results with a publication date between 1 October 2012 and 1 May 2025. This decision was made on the observation that significant research interest around MUCIs began to emerge in the early 2010s. By starting our review in 2012, we ensured coverage of the most relevant publications considering the rapid advances of conversational Artificial Intelligence (AI) in the last decade and reflecting the most current literature available at the time of this survey. Furthermore, we assumed that if techniques and methodologies published before 2012 are still in use in contemporary research, their approaches would be referenced or built upon in subsequent literature, and thus captured through our analysis of more recent works. The initial sample contained 186 publications. After a more detailed analysis, the papers that were unrelated or had only marginal relation to the topic of MUCIs were removed. The remaining articles were systematically and carefully reviewed to minimise bias and provide reliable results for the survey. We had to remove three duplicates and another publication which was not in English. Two publications were not accessible due to being hosted by non-open-access publishers, which prevented us from including them in the detailed analysis. Regarding the inclusion criteria, we considered only those articles that offered a description of the design process, implementation, or empirical evaluation of a MUCI. Eligible publications were required to present either a (prototypical) dialogue interface or to position multi-user human-machine interactions as the central aspect of the investigation. As a result, 121 retrieved articles were excluded because they did not meet these requirements. We identified three primary criteria for exclusion: absence of a conversational interface, insufficient support of multi-user interaction, or an unrelated thematic focus on network technology. More specifically, 61 articles were excluded because they described interfaces that did not support natural language dialogues between users and the system, relying instead on alternative interaction modalities such as graphical controls or keyboard input.