Comparing Semi-Automated Clustering Methods for Persona Development

Jonalan Brickey, Steven Walczak, Tony Burgess

Research output: Contribution to journalArticlepeer-review

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.

Original languageAmerican English
JournalIEEE Transactions on Software Engineering
Volume38
DOIs
StatePublished - Jun 1 2012

Keywords

  • clustering
  • interaction styles
  • personas
  • user-centered design
  • user interfaces

Disciplines

  • Management Information Systems
  • Management Sciences and Quantitative Methods

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