Human–Computer Interaction in Marketing: Emerging Interfaces, Cognitive Engagement, and Child–Computer Interaction

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Applications".

Deadline for manuscript submissions: 30 April 2026 | Viewed by 5535

Special Issue Editors


E-Mail Website
Guest Editor
Department of Management Science and Technology, University of Patras, Pátrai, Greece
Interests: neuromarketing; human–computer interaction; eye tracking; child–computer interaction; behavioral data analysis; structural equation modeling
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Centre National de la Recherche Scientifique (CNRS), ICube Lab UMR 7357 CNRS, Université de Strasbourg, F-67081 Strasbourg, France
Interests: cognitive neuroscience; brain; cognitive psychology; behavior; perceptual learning and memory; neural networks; consciousness; philosophy of artificial intelligence; principles of unsupervised learning; computing and philosophy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The intersection between human–computer interaction (HCI) and marketing presents a dynamic field of study with increasing relevance in both academic and applied contexts. As digital environments grow more interactive, personalized, and persuasive, understanding how users engage with marketing content—both cognitively and behaviorally—becomes essential.

This Special Issue seeks to explore cutting-edge research at the crossroads of HCI and marketing, with a special emphasis on emerging interfaces, cognitive engagement, and the evolving field of child–computer interaction in marketing contexts. Topics may include user experience and interface design, persuasive technologies, eye-tracking studies, emotional and attentional responses, and ethical considerations in interactive systems that target adults or children.

We invite interdisciplinary contributions from scholars working in the fields of HCI, digital marketing, communication, and education technology.

Topics of interest include, but are not limited to, the following:

  • Eye-tracking and attention in digital marketing;
  • UX/UI evaluation for persuasive systems and apps;
  • Child–computer interaction and advertising literacy;
  • Emotional and cognitive engagement in HCI;
  • Ethical and privacy issues in interactive marketing;
  • Neuromarketing and biometric data applications;
  • Augmented/virtual reality in brand interaction;
  • Personalized recommendations and AI-driven interfaces;
  • Behavioral and psychometric analyses of digital consumers.

We look forward to your valuable contributions to this Special Issue.

Dr. Stefanos Balaskas
Prof. Dr. Birgitta Dresp-Langley
Guest Editors

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Keywords

  • human–computer interaction
  • neuromarketing
  • eye tracking
  • digital advertising
  • user experience
  • child–computer interaction
  • persuasive technology
  • behavioral data analysis
  • ethical design

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Published Papers (4 papers)

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Research

20 pages, 501 KB  
Article
Does Follower Size Matter? Diversity of Sources and Credibility Assessment Among Social Media Influencers
by Halima Lul Ali, Faiswal Kasirye and Louisa Ha
Information 2025, 16(11), 958; https://doi.org/10.3390/info16110958 - 5 Nov 2025
Cited by 1 | Viewed by 2366
Abstract
This study investigates how follower size influences social media influencers’ sourcing behavior and credibility assessment rigor when producing content for their audiences. Grounded in Social Capital Theory, this study examines the tension between popularity as a form of social capital and its limited [...] Read more.
This study investigates how follower size influences social media influencers’ sourcing behavior and credibility assessment rigor when producing content for their audiences. Grounded in Social Capital Theory, this study examines the tension between popularity as a form of social capital and its limited capacity to predict rigorous credibility assessment using a global quantitative survey of 500 social media influencers across multiple languages and regions. The findings suggest that influencers with larger follower sizes utilize more diverse sources; however, follower size does not correlate with credibility assessment rigor. This underscores that follower size functions as a symbolic rather than epistemic resource, where source diversity often serves as a visible signal of professionalism rather than having a deeper verification. Additionally, credibility assessment rigor is not a significant predictor of source diversity, and platform type and content genre did not moderate the relationship between follower size and source diversity. These findings contribute to the influencer marketing literature by challenging assumptions linking popularity with higher scrutiny of content credibility. The study holds implications for platform policy, media literacy education, and influencer–brand collaborations. Recommendations are provided for improving transparency and source vetting among digital content creators in increasingly flooded social media platforms. Full article
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22 pages, 1065 KB  
Article
Mapping the Gaze: Comparing the Effectiveness of Bowel-Cancer Screening Advertisements
by Ioanna Yfantidou, Marek Palace, Stefanos Balaskas, Christian Von Wagner, Lee Smith, Brandon May, Jazzine Samuel, Meghna Srivastava, Carlos Santos Barea and Sandro Stoffel
Information 2025, 16(11), 935; https://doi.org/10.3390/info16110935 - 28 Oct 2025
Viewed by 756
Abstract
Public-health campaigns have to capture and hold visual attention, but little is known about the influence of message framing and visual appeal on attention to bowel-cancer screening ad campaigns. In a within-subjects test, 42 UK adults aged 40 to 65 viewed 54 static [...] Read more.
Public-health campaigns have to capture and hold visual attention, but little is known about the influence of message framing and visual appeal on attention to bowel-cancer screening ad campaigns. In a within-subjects test, 42 UK adults aged 40 to 65 viewed 54 static adverts that varied by (i) slogan frame—anticipated regret (AR) vs. positive (P); (ii) image type—hand-drawn, older stock, AI-generated; and (iii) identity congruence—viewer ethnicity matched vs. unmatched to the depicted models. Remote eye-tracking measured time to first fixation (TTFF), dwell, fixations, and revisits on a priori pre-defined regions of interest (ROIs); analyses employed linear mixed-effects models (LMMs), generalized estimating equations (GEEs), and median quantile regressions with cluster at the participant level. Across models, the AR slogans produced faster orienting (smaller TTFF) and more intense maintained attention (longer dwell, more fixations and revisits) than the P slogans. Image type set baseline attention (hand-drawn > old stock > AI) but did not significantly decrease the AR benefit, which was equivalent for all visual styles. Identity congruence enhanced early capture (lower TTFF), with small effects for dwell-based measures, suggesting that tailoring benefits only the “first glance.” Anticipated-regret framing is a reliable, design-level alternative to improving both initial capture and sustained processing of screening messages. In practice, the results indicate that advertisers should pair regret-based slogans with warm, human-centred imagery; place slogans in high-salience, low-competition spaces, and, when incorporating AI-generated imagery, reduce composition complexity and exclude uncanny details. These findings ground regret framing as a visual-attention mechanism for public-health campaigns in empirical fact and provide practical recommendations for testing and production. Full article
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28 pages, 6595 KB  
Article
Identifying Individual Information Processing Styles During Advertisement Viewing Through EEG-Driven Classifiers
by Antiopi Panteli, Eirini Kalaitzi and Christos A. Fidas
Information 2025, 16(9), 757; https://doi.org/10.3390/info16090757 - 1 Sep 2025
Viewed by 865
Abstract
Neuromarketing studies the brain function as a response to marketing stimuli. A large amount of neuromarketing research uses data from electroencephalography (EEG) recordings as a response of individuals’ brains to marketing stimuli, aiming to identify the factors that influence consumer behaviour that they [...] Read more.
Neuromarketing studies the brain function as a response to marketing stimuli. A large amount of neuromarketing research uses data from electroencephalography (EEG) recordings as a response of individuals’ brains to marketing stimuli, aiming to identify the factors that influence consumer behaviour that they cannot articulate or are reluctant to reveal. Evidence suggests that individuals’ processing styles affect their reaction to marketing stimuli. In this study, we propose and evaluate a predictive model that classifies consumers as verbalizers or visualizers based on EEG signals recorded during exposure to verbal, visual, and mixed advertisements. Participants (N = 22) were categorized into verbalizers and visualizers using the Style of Processing (SOP) scale and underwent EEG recording while viewing ads. The EEG signals were preprocessed and the five EEG frequency bands were extracted. We employed three classification models for every set of ads: SVM, Decision Tree, and kNN. While all three classifiers performed around the same, with accuracy between 86 and 93%, during cross-validation SVM proved to be the more effective model, with kNN and Decision Tree showing sensitivity to data imbalances. Additionally, we conducted independent t-tests to look for statistically significant differences between the two classes. The t-tests implicated the Theta frequency band. Therefore, these findings highlight the potential of leveraging EEG-based technology to effectively predict a consumer’s processing style for advertisements and offers practical applications in fields such as interactive content designs and user-experience personalization. Full article
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16 pages, 2093 KB  
Article
Neuromarketing and Health Marketing Synergies: A Protection Motivation Theory Approach to Breast Cancer Screening Advertising
by Dimitra Skandali, Ioanna Yfantidou and Georgios Tsourvakas
Information 2025, 16(9), 715; https://doi.org/10.3390/info16090715 - 22 Aug 2025
Cited by 1 | Viewed by 994
Abstract
This study investigates the psychological and emotional mechanisms underlying women’s reactions to breast cancer awareness advertisements through the dual lens of Protection Motivation Theory (PMT) and neuromarketing methods, addressing a gap in empirical research on the integration of biometric and cognitive approaches in [...] Read more.
This study investigates the psychological and emotional mechanisms underlying women’s reactions to breast cancer awareness advertisements through the dual lens of Protection Motivation Theory (PMT) and neuromarketing methods, addressing a gap in empirical research on the integration of biometric and cognitive approaches in health marketing. Utilizing a lab-based experiment with 78 women aged 40 and older, we integrated Facial Expression Analysis using Noldus FaceReader 9.0 with semi-structured post-exposure interviews. Six manipulated health messages were embedded within a 15 min audiovisual sequence, with each message displayed for 5 s. Quantitative analysis revealed that Ads 2 and 5 elicited the highest mean fear scores (0.45 and 0.42) and surprise scores (0.35 and 0.33), while Ad 4 generated the highest happiness score (0.31) linked to coping appraisal. Emotional expressions—including fear, sadness, surprise, and neutrality—were recorded in real time and analyzed quantitatively. The facial analysis data were triangulated with thematic insights from interviews, targeting perceptions of threat severity, vulnerability, response efficacy, and self-efficacy. The findings confirm that fear-based appeals are only effective when paired with actionable coping strategies, providing empirical support for PMT’s dual-process model. By applying mixed-methods analysis to the evaluation of health messages, this study makes three contributions: (1) it extends PMT by validating the emotional–cognitive integration framework through biometric–qualitative convergence; (2) it offers practical sequencing principles for combining threat and coping cues; and (3) it proposes cross-modal methodology guidelines for future health campaigns. Full article
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