How Does Personification Impact Ad Performance and Empathy? An Experiment with Online Advertising
This research, led by Joni Salminen, explores the value of personas for supporting professional advertisers designing social media advertising.
December 2020
APG Data-Driven Persona Research Published 2020
The APG Team and collaborators have been pushing, perhaps defining, the field of data-driven personas with host of research articles published so far in 2020. We provide the articles and please reach out if interested in collaboration or if you have questions about specific research. Would be great to hear from you!
Privacy Personas in the MENA Region: A Large-Scale Analysis of 21 Countries
Beginning January 2021, the APG Team is leading a digital privacy project funded via a research award from Facebook. We thank the researchers at Facebook for their interest in and support of this project.
Chapters for Data-Driven Personas, a Morgan-Claypool Publication
We are putting the finished touches on our book, Data-Driven Personas by Bernard J. Jansen, Joni O. Salminen, Soon-Gyo Jung, and Kathleen Guan, Hamad Bin Khalifa University (HBKU) and University College London. Morgan & Claypool Publishers. The book is comprised of 12 chapters (10 content chapters, plus an introduction and conclusion chapter) divided into 6 …
Chapters for Data-Driven Personas, a Morgan-Claypool Publication Read More »
Acknowledgements for Data-Driven Personas, a Morgan-Claypool Publication
We are almost finished with our book, Data-Driven Personas by Bernard J. Jansen, Joni O. Salminen, Soon-Gyo Jung, and Kathleen Guan, Hamad Bin Khalifa University (HBKU) and University College London. Morgan & Claypool Publishers. Sending out some acknowledgements early
Making Meaningful User Segments from Datasets Using Product Dissemination and Product Impact
As paper-based personas move to interactive persona analytics systems, online companies face large user populations, making segmentation a daunting exercise, along with creating actionable data-driven personas from these large datasets. In this research, we demonstrate an approach that facilitates user segmentation. The approach leverages product dissemination and product impact metrics with normalized Shannon entropy.