Jim Jansen

Dr. Jansen is a Principal Scientist in the social computing group of the Qatar Computing Research Institute, and a professor with the College of Science and Engineering, Hamad bin Khalifa University, and an adjunct professor with the College of Information Sciences and Technology at The Pennsylvania State University. He is a graduate of West Point and has a Ph.D. in computer science from Texas A&M University, along with master degrees from Texas A&M (computer science) and Troy State (international relations). Dr. Jim Jansen served in the U.S. Army as an Infantry enlisted soldier and communication commissioned officer.

How does varying the number of personas affect user perceptions and behavior? Challenging the ‘small personas’ hypothesis!

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Studies in human-computer interaction recommend creating fewer than ten personas based on stakeholders’ limitations to cognitively process and use personas. However, no existing studies offer empirical support for having fewer rather than more personas. Investigating this matter, thirty-seven participants interacted with five and fifteen personas using an interactive persona system, choosing one persona to design […]

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Big Data, Small Personas: How Algorithms Shape the Demographic Representation of Data-Driven User Segments

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Derived from the notion of algorithmic bias, it is possible that creating user segments such as personas from data results in over- or under-representing certain segments (FAIRNESS), does not properly represent the diversity of the user populations (DIVERSITY), or produces inconsistent results when hyperparameters are changed (CONSISTENCY). Collecting user data on 363M video views from

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Persona Analytics: a pathway to persona science

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Slidedeck on Persona Analytics: pathway to persona science from QUANT UX Conference 2022 https://drive.google.com/file/d/1euyQPqUdVd0B8r249SApNOyN6hzESf2n/view Salminen, J., Jung, S.G., and Jansen, B. J. (2022) Persona Analytics: a pathway to persona science. In CN Chapman, KZ Xu, M Callegaro, F Gao, and M Cipollone, eds. (2022). Proceedings of the 2022 Quantitative User Experience Conference (Quant UX Con).

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Personas as a Exploratory Data Analysis Technique

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Exploratory data analysis (EDA) explores and analyzes a data set using descriptive statistics and visualizations to learn about the dataset. The main motivations for EDA are: detecting data errors testing assumptions about the data selecting appropriate models determining relationships among the explanatory variables accessing the direction and magnitude relationships between explanatory and outcome variables. However,

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Algorithmically-Generated Personas paired with AI-Generated Pain Points Detection

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One does not often hear personas, AI, and pain points mentioned together. However, the combination can provide better situational awareness and better brainstorming on addressing customer pain points. It is analogous to a mixed-methods approach!   Artificial intelligence carries a high potential to automatically detect customers’ pain points, which is a particular concern the customer

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Personas: a data visualization technique

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Although often touted as a design technique, personas are more accurately viewed as a data visualization option, similar to tables, charts, or graphs. Personas were proposed to represent perceived users, customers, or audience members. In practice. personas are often used to represent current users, customers, or audience members. Personas can be a valuable data visualization

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Generate Personas from GA4 Data

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What does using Google Analytics 4 mean for algorithmically generating personas? Google Analytics 4 (GA4) is an analytics service that measures traffic and engagement across websites and apps.  With the forced move from Google Universal Analytics (UA), a.k.a., Google Analytics, to GA4, on July 1, 2023, web properties using Universal Analytics will no longer be

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