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HCI and data-driven personas Persona Creation Persona Design Persona Development Personas

Elements of a Persona Profile

Persona and Persona Profile

A persona is a humanized representation of a user segment, audience segment, or customer segment.

The persona is presented in a persona profile. A persona profile is the actual representation of the persona. So, a persona is a conceptualize. The person profile is the physical manifestation of that concept.

The persona profile contains various attributes, insights, and information about the persona. Each of these are an element of the persona profile.

Example of a Persona Profile

Here is an example of a data-driven persona profile created by APG, the automated persona generation system.

APG affords the ability to increase or reduce the number of personas in real time!
This is a persona profile generated by APG, which is a full stack persona analytics system.

What elements does a persona profile typically contain?

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Automatic Persona Generation Data-Driven Personas Persona Creation Persona Design Persona Development Personas Use of Personas User Personas

How suitable are artificially generated facial pictures in data-driven personas?

In a previous post, we analyzed the demographic Bias in Artificially Generated Facial Pictures that raised a concern that the generated images might not fairly represent all demographic groups.

In this post, we discuss if these artificially generated pictures are good enough for use in personas profiles for real-world systems and applications,  which are highly dependent on images for the personas. One of the key aspects of generating personas using a data-driven approach is to be able to represent the persona profile with a matching picture.

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Persona Creation Persona Design Persona Development Persona Research Personas

Persona Transparency: Analyzing the Impact of Explanations on Perceptions of Data-Driven Persona

Persona Transparency: Analyzing the Impact of Explanations on Perceptions of Data-Driven Personas

Persona Transparency: Analyzing the Impact of Explanations on Perceptions of Data-Driven Personas

Computational techniques are becoming more common in persona development. However, users of personas may question the information in persona profiles because they are unsure of how it was created.

This problem is especially vexing for data-driven personas because their creation is an opaque algorithmic process. 

In this research, we analyze the effect of increased transparency – i.e., explanations of how the information in data-driven personas was produced – on user perceptions. 

We find that higher transparency through these explanations increases the perceived completeness and clarity of the personas. 

Contrary to  our hypothesis, the perceived credibility of the personas decreases with the increased transparency, possibly due to the technical complexity of the persona profiles disrupting the facade of the personas being real people. 

This finding suggests that explaining the algorithmic process of data-driven persona creation involves a “transparency trade-off”. 

We also find that the gender of the persona affects the perceptions, with transparency increasing perceived completeness and empathy of the female persona, but not for the male persona. Therefore, transparency may specifically assist in the acceptance of female personas. 

We provide practical implications for persona creators regarding transparency in persona profiles.

Read Full Research

Salminen, J., Santos, J., Jung, S. G., Eslami, M. and Jansen, B. J. (2020) Persona Transparency: Analyzing the Impact of Explanations on Perceptions of Data-Driven PersonasInternational Journal of Human-Computer Interaction, 36(8), 788-800.

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CHI Persona Creation Persona Design Persona Development Persona Research Personas

Analyzing Demographic Bias in Artificially Generated Facial Pictures

Artificial generation of facial images is increasingly popular, with machine learning achieving photo-realistic results.

Yet, there is a concern that the generated images might not fairly represent all demographic groups. This has implications for persona development when approaching the goal of generating the facial pictures for the persona profiles automatically.

Analyzing Demographic Bias in Artificially Generated Facial Pictures
Analyzing Demographic Bias in Artificially Generated Facial Pictures

In research led by Joni Salminen, we use a state-of-the-art method to generate 10,000 facial images and observe that the generated images are skewed towards young people, especially white women.

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Data-Driven Personas Persona Design Persona System

How APG Assigns Pictures to Create Data-Driven Personas

The following is a post from the APG Team’s summer 2020 intern, Jaad Mohammed.
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If you have ever wondered how photos or headshots are assigned to a persona profile by the AGP system? Well, you’ve come to the right place.

First, you need to understand where exactly APG collects data and how it processes this data to create the basic structure for a set of base personas.

APG links to and accesses data from online social media platforms (e.g., Facebook, Google Analytics, YouTube) via the Application Program Interface (API) of each analytics platform, given an account holder’s permission [1]

Via the APIs, APG collects the detailed interactions of users with each of the online content pieces on the corresponding platform. This data is available to only owners of a particular social media channel (e.g., YouTube channel) and is not available to the general public

Data provided by these API’s contain variables of gender, age, and country of the set of users, audience members, or customers, provided at an aggregated group level.

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Automatic Persona Generation Personas

Giving Faces to Data by Creating Data-Driven Personas

APG logo with three team members
Giving Faces to Data: Creating Data-Driven Personas from Personified Big Data

Creating personas from large amounts of online data is useful but difficult with manual methods.

To address this difficulty, we present Automatic Persona Generation (APG), which is an implementation of a methodology for quantitatively generating data-driven personas from online social media data.

APG is functional, and it is deployed with several organizations in multiple industry verticals.

APG employs a scalable web front-end user interface and robust back-end database framework processing tens of millions of user interactions with tens of thousands of online digital products across multiple online platforms, including Facebook, Google Analytics, and YouTube.

APG identifies audience segments that are both distinct and impactful for an organization to create persona profiles. APG enhances numerical social media data with relevant human attributes, such as names, photos, topics, etc. Here, we discuss the architecture development and central system features.

Overall, APG can benefit organizations in distributing content via online platforms or with online content that relates to commercial products. APG is unique in its algorithmic approach to processing social media data for customer insights. APG can be found online at https://persona.qcri.org.

Here is a two pager about the Automatic Persona Generation (APG) system!

Read full article

Jung, S.G., Salminen, J., and Jansen, B. J. (2020) Giving Faces to Data: Creating Data-Driven Personas from Personified Big Data. ACM Conference on Intelligent User Interfaces (IUI2020)(Demo Paper), Cagliari, Italy. 17-20 March, 132-133

Read more about data-driven personas

What is a Data-Driven Persona?

Introduction to Data-Driven Personas

Benefits of Data-Driven Personas

Explaining Data-Driven Personas to End Users

Got too many personas? This approach can help!

Do your think your personas are stable? They probable aren’t!

 

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Persona Creation Persona Design Persona Research Personas

The Effect of Smiling Pictures on Perceptions of Personas

In this research on impact of smile on persona perceptions with Soon-gyo Jung, João Santos, and Jim Jansen, we find that persona profiles with a smiling photo result in an increase in perceived similarity with, likability of, and willingness to use a persona.

However, a smile does not increase the credibility of a persona. Our research has implications for the design of persona profiles and adds to previous findings of persona research that the picture choice influences individuals’ persona perceptions in profound ways.

persona smiles

Salminen, J. Jung, S.G., Santos, J.M., and Jansen, B. J. (2019). The Effect of Smiling Pictures on Perceptions of Personas. User Modelling, Adaptation and Personalization (UMAP19). Larnaca, Cyprus. 9–12 June 2019.