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A Survey of 15 Years of Data-Driven Persona Development




TekijätSalminen Joni, Guan Kathleen, Jung Soon-Gyo, Jansen Bernard J.

KustantajaTaylor & Francis

Julkaisuvuosi2021

JournalInternational Journal of Human-Computer Interaction

Tietokannassa oleva lehden nimiINTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION

Lehden akronyymiINT J HUM-COMPUT INT

Sivujen määrä24

ISSN1044-7318

eISSN1532-7590

DOIhttps://doi.org/10.1080/10447318.2021.1908670

Verkko-osoitehttps://www.tandfonline.com/doi/full/10.1080/10447318.2021.1908670

Rinnakkaistallenteen osoitehttps://research.utu.fi/converis/portal/detail/Publication/56622282


Tiivistelmä
Data-driven persona development unifies methodologies for creating robust personas from the behaviors and demographics of user segments. Data-driven personas have gained popularity in human-computer interaction due to digital trends such as personified big data, online analytics, and the evolution of data science algorithms. Even with its increasing popularity, there is a lack of a systematic understanding of the research on the topic. To address this gap, we review 77 data-driven persona research articles from 2005-2020. The results indicate three periods: (1) Quantification (2005-2008), which consists of the first experiments with data-driven methods, (2) Diversification (2009-2014), which involves more pluralistic use of data and algorithms, and (3) Digitalization (2015-present), marked by the abundance of online user data and the rapid development of data science algorithms and software. Despite consistent work on data-driven personas, there remain many research gaps concerning (a) shared resources, (b) evaluation methods, (c) standardization, (d) consideration for inclusivity, and (e) risk of losing in-depth user insights. We encourage organizations to realistically assess their data-driven persona development readiness to gain value from data-driven personas.

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Last updated on 2024-26-11 at 18:25