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.

Personas for your non-customers – the Edge, the Refuse, and Unknown non-customers

Personas can be a force multiplier in reaching your three categories of non-customers – the Edge Non-customers, the Refuse Non-customers, and Unknown Non-customers. Algorithmically-Generated Personas are great for humanized representation of your existing customers presented in understandable chunks of information. These data-driven personas are great for team communication while creating content and designing systems, along …

Personas for your non-customers – the Edge, the Refuse, and Unknown non-customers Read More »

Qualitative Personas: Strengths and Weaknesses

Personas are a technique for enhanced understanding of users and customers to improve the user-centered design of systems and products. Their creation can be categorized using three persona creation methodologies: Qualitative, Quantitative, and Mixed Methods. In this post, we describe the Qualitative method and discuss the strengths and weaknesses of this methodology for persona development. …

Qualitative Personas: Strengths and Weaknesses Read More »

Creating More Personas Improves Representation of Demographically Diverse Populations: Implications Towards Interactive Persona Systems

Personas represent distinct user types. However, while online user data can be demographically and behaviorally heterogeneous, most studies generate less than ten personas, regardless of how heterogeneous the data is. Because all persona creation efforts need to assign a number of personas to create, assigning this number evokes a fundamental question, How many personas to …

Creating More Personas Improves Representation of Demographically Diverse Populations: Implications Towards Interactive Persona Systems Read More »

Intentionally Biasing User Representation?: Investigating the Pros and Cons of Removing Toxic Quotes from Social Media Personas

Algorithmically generated personas can help organizations understand their social media audiences. However, when using algorithms to create personas from social media user data, the resulting personas may contain toxic quotes that negatively affect content creators’ perceptions of the personas. To address this issue, we have implemented toxicity detection in an algorithmic persona generation system capable …

Intentionally Biasing User Representation?: Investigating the Pros and Cons of Removing Toxic Quotes from Social Media Personas Read More »

Persona Preparedness: A Survey Instrument for Measuring the Organizational Readiness for Deploying Personas

Organizational user-centric design is crucial for developing information technology that offers optimal usability and user experience. Personas are a central user-centered design technique that puts people before technology and helps decision makers understand the needs and wants of the end-user segments of their products, systems, and services. However, it is not clear how ready organizations …

Persona Preparedness: A Survey Instrument for Measuring the Organizational Readiness for Deploying Personas Read More »

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

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 …

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

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

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 …

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