Enterprise social network messaging sites are becoming increasingly popular for team communication in engineering and product design. These digital communication platforms capture detailed messages between members of the design team and are an appealing data set for researchers who seek to better understand communication in design. This exploratory study investigates whether we can use enterprise social network messages to model communication patterns throughout the product design process. We apply short text topic modelling (STTM) to a data set comprising 250,000 messages sent by 32 teams enrolled in a 3-month intensive product design course. Many researchers describe the engineering design process as a series of convergent and divergent thinking stages, such as the popular double diamond model, and we use this theory as a case study in this work. Quantitative and qualitative analysis of STTM results reveals several trends, such as it is indeed possible to see evidence of cyclical convergence and divergence of topics in team communication; within the convergence–divergence pattern, strong teams have fewer topics in their topic models than weaker teams; and teams show characteristics of product, project, course, and other themes within each topic. We provide evidence that the analysis of enterprise social networking messages, with advanced topic modelling techniques, can uncover insights into design processes and can identify the communication patterns of successful teams.

Online communication and collaboration tools are changing the way teams design products. The tools also generate a rich data source from which to study trends in communication. This paper focuses on how engineering teams utilize Slack, a popular team messaging software platform. We aim to better understand communication and coordination in product design teams via analysis of team social network dynamics, unique patterns of chat-like messaging (emoji usage), and the evolution of communication topics over time.Our study analyzes the online interactions of 32 teams, sent during a 3-month senior undergraduate product design course. These 400,000+ messages represent the team communications from 4 years of teams, with 17-20 students per team.We find that 1) Slack communications resulted in high density network maps, 2) network analysis of teams reveals that leaders have more central positions in the network, 3) strong teams have lower average centrality among members, equivalent to less public channel membership per person, 4) stronger teams use emojis at a higher rate, and 5) emojis are used most by leaders and highly connected members.These findings represent preliminary foundations for best practices in online messaging, which may lead to more effective collaboration in product design. INTRODUCTIONCommunication, key to the engineering design process, is being disrupted by new technological developments changing the ways by which teams collaborate in the classroom and the workplace. Teams worldwide are adopting online communication software for information sharing, documentation, project management, collaboration, and decision making. Slack, an online message-based communication software, has become a staple tool for student and industry engineers alike, with tens of millions of users [1] . Slack not only facilitates team messaging, but also supports a variety of project management and external integrations [2] . These software platforms unlock data for quantitative analysis of design team communication and collaboration, from which we can identify patterns of virtual communication content, timing, and organization.Previous studies have analyzed email communication of engineering teams [3] , or the use of Slack by software development teams [4,5] and Information Technology enterprises [6] . This paper focuses on student product design teams, building on previous work [7] . We analyze 400,000+ virtual interactions sent by 32 different teams over the span of three months, as they progress through the stages of product design, from ideation to alpha prototype launch.We explore the intricacies of the individual contributions and dynamics within teams through network analysis, emoji frequency analysis, and topic modelling of electronic communications. Each team, having unique communication