Q&A with Clemson College’s Bart Knijnenburg, analysis award recipient for bettering advert experiences
In this monthly series of interviews, we put members of the academic community and their important research in the spotlight – as partners, employees, consultants or independent collaborators.
For February we have nominated Bart Knijnenburg, Assistant Professor at Clemson University. Knijnenburg is a UX-sponsored research award recipient for Improving the Ad Experience in 2019, the results of which were nominated for Best Paper at the 54th Hawaii International Conference on System Sciences (HICSS). Knijnenburg was also involved in the Facebook scholarship program as an advisor to two program alumni, Moses Namara and Daricia Wilkinson.
In this Q&A, Knijnenburg describes his work at Clemson, including his recently nominated research to improve the ad experience. He also tells us what inspired this research, what the results were, and where people can learn more.
Q: Tell us about your role at Clemson and the type of research that you and your department specialize in.
Bart Knijnenburg: I am an assistant professor in the Human-Centered Computing department at the Clemson University School of Computing. Our department studies the human aspects of computing through user-centered design and user experimentation with faculty members exploring virtual environments, online communities, adaptive user experiences, etc. My personal interest is in helping people make better decisions online through adaptive support for consumer choices. In this broad area I have specialized in usable recommendation systems and data protection decisions.
In the area of recommendation systems, I focus on useful mechanisms with which users of such systems can enter their preferences and on novel means of displaying the resulting recommendations and explaining them to users. An important goal in this area is to create systems that not only display user elements that reflect their preferences, but also help users better understand their preferences – systems that I refer to as “self-actualization recommender systems.”
In the area of privacy decision making, I focus on systems that actively assist consumers in their privacy decision making practices – a concept I have termed “user-centric privacy”. These systems are designed to help users translate their privacy settings into settings, thereby reducing the control burden on users while respecting their inherent privacy settings.
Q: What inspired you to continue your current research on improving the ad experience?
BK: Despite recent efforts to improve the user experience with online ads, there is increasing distrust and skepticism about the collection and use of personal data for advertising purposes. There are a number of reasons for this suspicion, including a lack of transparency and control. This lack of visibility and control not only creates suspicion, but also makes it more likely that the user models created by ad personalization algorithms will reflect users’ immediate desires rather than their longer-term goals. The ads presented, in turn, reflect these short-term preferences and ignore the ambitions of the users and their better selves.
As someone who has dealt extensively with transparency and control in both recommendation systems and privacy, I am excited to apply this work to the ad experience space. In this project, my team would like to design, create, and evaluate intuitive explanations of the ad recommendation process and interaction mechanisms that users can use to control this process. We will build these mechanisms in line with the emerging concepts of recommendation systems for self-actualization and custom privacy. The ultimate goal of this effort is to better align advertising with users’ long-term goals and ambitions.
Q: What were the results of this research?
BK: The work on this project is still very far advanced. Our first step was to conduct a systematic literature search on advertisement declarations that covers existing research on how they are generated, presented and perceived by users. Based on this review, we have developed a classification scheme that categorizes the existing literature on ad statements and provides insight into the reasons for the ad recommendation, the purpose of the statement, the content of the statement, and the presentation of that content. This classification scheme provides a useful tool for researchers and practitioners to aggregate existing research into advertisement statements and identify avenues for future research.
Our second step involves developing a measurement tool to evaluate ad experience. The validation of this measuring instrument is still ongoing. However, the end result will include a carefully crafted set of questionnaires that can be used for user responses to online ads, including aspects of targeting, accountability, transparency, control, reliability, persuasion. and creepiness.
A third step involves a fundamental redesign of the advertising experience on social networks, redefining the concept of advertising as a means to an end that serves the user’s longer-term goals. We are at the very early stages of this activity, but we would like to explore the paradigm of recommendations, insights, and / or personal goals as vehicles for this transformation of the ad experience.
Q: How has this research been received so far?
BK: Our contribution to the literature research and the classification scheme for advertising declarations was accepted by HICSS and nominated as the best article in the minitrack Social Media and E-Business Transformation. We are working on an interactive version of the classification scheme, which will provide a convenient overview of the most important research results in the area of advertisement declarations and direct access to them.
We also work with Facebook researchers to ensure that our ad experience measurement tool is optimally suited to delivering a user-friendly ad experience.
Q: Where can people find out more about your research?
BK: You can find a project page on this research at www.usabart.nl/FBads. We will keep this page updated as soon as new results are available!