Explaining data-driven personas to end users

Soon Gyo Jung, Joni Salminen, Bernard J. Jansen

Research output: Contribution to journalConference articlepeer-review


Enabled by digital user data and algorithms, persona user interfaces (UI) are moving to digital formats. However, algorithms and user data, if left unexplained to end users, might leave data-driven personas (DDPs) difficult to understand and trust. This is because the data and the way it is processed are complex and not self-evident, requiring explanations of the DDP information and UIs. In this research, we provide a proof of concept for adding transparency to DDP using a real system UI. Furthermore, we demonstrate ways to add breakdown information that can help alleviate user stereotyping associated with the use of personas.

Original languageEnglish (US)
JournalCEUR Workshop Proceedings
StatePublished - Jan 1 2020
Event2020 Workshop on Explainable Smart Systems for Algorithmic Transparency in Emerging Technologies, ExSS-ATEC 2020 - Cagliari, Italy
Duration: Mar 17 2020 → …

All Science Journal Classification (ASJC) codes

  • Computer Science(all)


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