Communication patterns in engineering enterprise social networks: an exploratory analysis using short text topic modelling
Name
communication-patterns-in-engineering-enterprise-social-networks-an-exploratory-analysis-using-short-text-topic-modelling.pdf
Description
Published version
Size
1.16 MB
Format
Adobe PDF
Checksum (MD5)
5bf23e6bb248140108131cf489a28378
Author(s)
Ferguson, Sharon A.
Cheng, Kathy
Adolphe, Lauren
Van de Zande, Georgia
Wallace, David
Olechowski, Alison
Date Issued
2022
Journal
Design Science
Publisher
Cambridge University Press
Citation
Ferguson SA, Cheng K, Adolphe L, Van de Zande G, Wallace D, Olechowski A. Communication patterns in engineering enterprise social networks: an exploratory analysis using short text topic modelling. Design Science. 2022;8:e18.
Version
Final published version
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.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1017/dsj.2022.12
