Comparing Semi-Automated Clustering Methods for Persona Development
Document Type
Article
Publication Date
6-2012
Keywords
clustering, interaction styles, personas, user-centered design, user interfaces
Digital Object Identifier (DOI)
https://doi.org/10.1109/TSE.2011.60
Abstract
Current and future information systems require a better understanding of the interactions between users and systems in order to improve system use and, ultimately, success. The use of personas as design tools is becoming more widespread as researchers and practitioners discover its benefits. This paper presents an empirical study comparing the performance of existing qualitative and quantitative clustering techniques for the task of identifying personas and grouping system users into those personas. A method based on Factor (Principal Components) Analysis performs better than two other methods which use Latent Semantic Analysis and Cluster Analysis as measured by similarity to expert manually defined clusters.
Was this content written or created while at USF?
No
Citation / Publisher Attribution
IEEE Transactions on Software Engineering, v. 38, issue 3, p. 537-546
Scholar Commons Citation
Brickey, Jonalan; Walczak, Steven; and Burgess, Tony, "Comparing Semi-Automated Clustering Methods for Persona Development" (2012). School of Information Faculty Publications. 173.
https://digitalcommons.usf.edu/si_facpub/173
