TY - JOUR
T1 - Creating user stereotypes for persona development from qualitative data through semi-automatic subspace clustering
AU - Korsgaard, Dannie Michael
AU - Bjørner, Thomas
AU - Sørensen, Pernille Krog
AU - Burelli, Paolo
PY - 2020
Y1 - 2020
N2 - Personas are models of users that incorporate motivations, wishes, and objectives; These models are employed in user-centred design to help design better user experiences and have recently been employed in adaptive systems to help tailor the personalized user experience. Designing with personas involves the production of descriptions of fictitious users, which are often based on data from real users. The majority of data-driven persona development performed today is based on qualitative data from a limited set of interviewees and transformed into personas using labour-intensive manual techniques. In this study, we propose a method that employs the modelling of user stereotypes to automate part of the persona creation process and addresses the drawbacks of the existing semi-automated methods for persona development. The description of the method is accompanied by an empirical comparison with a manual technique and a semi-automated alternative (multiple correspondence analysis). The results of the comparison show that manual techniques differ between human persona designers leading to different results. The proposed algorithm provides similar results based on parameter input, but was more rigorous and will find optimal clusters, while lowering the labour associated with finding the clusters in the dataset. The output of the method also represents the largest variances in the dataset identified by the multiple correspondence analysis.
AB - Personas are models of users that incorporate motivations, wishes, and objectives; These models are employed in user-centred design to help design better user experiences and have recently been employed in adaptive systems to help tailor the personalized user experience. Designing with personas involves the production of descriptions of fictitious users, which are often based on data from real users. The majority of data-driven persona development performed today is based on qualitative data from a limited set of interviewees and transformed into personas using labour-intensive manual techniques. In this study, we propose a method that employs the modelling of user stereotypes to automate part of the persona creation process and addresses the drawbacks of the existing semi-automated methods for persona development. The description of the method is accompanied by an empirical comparison with a manual technique and a semi-automated alternative (multiple correspondence analysis). The results of the comparison show that manual techniques differ between human persona designers leading to different results. The proposed algorithm provides similar results based on parameter input, but was more rigorous and will find optimal clusters, while lowering the labour associated with finding the clusters in the dataset. The output of the method also represents the largest variances in the dataset identified by the multiple correspondence analysis.
KW - Ethnography
KW - Mixed method
KW - Older adults
KW - Persona
KW - Subspace clustering
UR - http://www.scopus.com/inward/record.url?scp=85077529989&partnerID=8YFLogxK
U2 - 10.1007/s11257-019-09252-5
DO - 10.1007/s11257-019-09252-5
M3 - Journal article
SN - 0924-1868
VL - 30
SP - 81
EP - 125
JO - User Modeling and User-Adapted Interaction
JF - User Modeling and User-Adapted Interaction
IS - 1
ER -