TY - CHAP
T1 - How designers talk: Constructing and analysing a design thinking data corpus
AU - Lloyd, Peter
AU - Salah, Almila Akdag
AU - Chandrasegaran, Senthil
PY - 2021
Y1 - 2021
N2 - A necessary condition of understanding how designers work is understanding how designers talk. In this paper we show how new methods of linguistic data analysis are beginning to reveal insights into the general nature of design conversations. For the first time we combine design activity data collected over 30 years by the Design Thinking Research Symposium (DTRS) ‘shared data’ series into a single corpus. We apply emerging techniques of analysis on this corpus and explore word forms, expressions, topics, and themes related to the particularities of how designers talk. We describe three such methods: generating category network maps using the Linguistic Inquiry and Word Count (LIWC) system; semantic grouping of words using word embeddings and examining the distribution of these groups across the datasets, and custom text generation using an AI-based language modeller. In applying these methods, we show that exploring design activity data at the corpus level can reveal more general patterns of design talk and raise key questions and hypotheses for further study. We see these methods as a first step in developing an understanding of how people not considered to be designers (e.g., scientists, business people, politicians) talk in ways that might be considered ‘designerly’ [1].
AB - A necessary condition of understanding how designers work is understanding how designers talk. In this paper we show how new methods of linguistic data analysis are beginning to reveal insights into the general nature of design conversations. For the first time we combine design activity data collected over 30 years by the Design Thinking Research Symposium (DTRS) ‘shared data’ series into a single corpus. We apply emerging techniques of analysis on this corpus and explore word forms, expressions, topics, and themes related to the particularities of how designers talk. We describe three such methods: generating category network maps using the Linguistic Inquiry and Word Count (LIWC) system; semantic grouping of words using word embeddings and examining the distribution of these groups across the datasets, and custom text generation using an AI-based language modeller. In applying these methods, we show that exploring design activity data at the corpus level can reveal more general patterns of design talk and raise key questions and hypotheses for further study. We see these methods as a first step in developing an understanding of how people not considered to be designers (e.g., scientists, business people, politicians) talk in ways that might be considered ‘designerly’ [1].
UR - https://www.mendeley.com/catalogue/5a54eec1-50aa-3828-ab5d-ace02f8037c2/
U2 - 10.1115/DETC2021-71200
DO - 10.1115/DETC2021-71200
M3 - Chapter
SN - 9780791885420
T3 - Proceedings of the ASME Design Engineering Technical Conference
BT - Proceedings of the ASME Design Engineering Technical Conference
PB - The American Society of Mechanical Engineers(ASME)
ER -