Communication patterns in engineering enterprise social networks: an exploratory analysis using short text topic modelling

Abstract

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.

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Visualizing design project team and individual progress using NLP: a comparison between latent semantic analysis and Word2Vector algorithms

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