Abstract
User experience design and subsequent usability evaluation can benefit from knowledge about user interaction, types, deployment settings and situations. Most of the time, the user type and generic requirements are given or can be obtained and used to model interaction during the design phase. The deployment settings and situations can be collected through the needfinding phase, either via user feedback or via the automatic analysis of existing data. Personas may be defined using the aforementioned information through user research analysis or data analysis. This work utilizes an approach to activate an accurate persona definition early in the design cycle, using topic detection to semantically enrich the data that are used to derive the persona details. This work uses Twitter data from a music event to extract information that can be used to assist persona creation. A user study in persona construction compares the topic modelling metadata to a traditional user collected data analysis for persona construction. The results show that the topic information-driven constructed personas are perceived as having better clarity, completeness and credibility. Additionally, the human users feel more attracted and similar to such personas. This work may be used to model personas and recommend suitable ones to designers of other products, such as advertisers, game designers and moviegoers.
Highlights
Personas are constructs that represent user archetypes and have been used extensively in various stages of human-computer interaction design
Building on the identified shortcomings of the manual and the data-generated persona construction and their individual advantages, this paper proposes a hybrid approach that is simple enough to apply, yet contextual and analytical so as to provide useful insights
All the aforementioned identified issues related to the collection of data, analysis of the persona attributes, construction and use of personas result in problems that end users, designers, marketeers and researchers face [38,39]
Summary
Personas are constructs that represent user archetypes and have been used extensively in various stages of human-computer interaction design. Generated personas address challenge 1 and 2 by utilizing web data to automatically create a number of personas, requiring minimal human involvement They cannot address trustworthiness and inaccuracy over time. Designer-generated personas are costly and take time to create They may be biased by their creators. They generally address challenges 3 and 4 better than automatically created personas, since designers may pick sources and specific data that seem trustworthy, as well as selecting representative information that they deem to be as futureproof as possible. Building on the identified shortcomings of the manual and the data-generated persona construction and their individual advantages, this paper proposes a hybrid approach that is simple enough to apply, yet contextual and analytical so as to provide useful insights.
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