User Attention Research Articles

Facial Coding Study of the Effect of Halal Claims on Purchase Intention of Electronic Products: Linking Maslow's Hierarchy of Needs Theory

Usability testing plays a pivotal role in assessing user experience on websites, providing businesses with invaluable insights into customer perspectives. Eye-tracking, a widely accepted methodology, zeroes in on visual engagement by analyzing specific Areas of Interest (AOI). This study embarked on an exploration of the impact of AOI on dwell time for the latest iteration of the Waters website and further delineated the sections that captivated the most and least user attention. Adopting a quantitative stance, a two-way ANOVA was deployed on a sample comprising 15 master’s students from two distinct academic institutions. Preliminary findings underscore significant disparities in dwell times across different AOIs, implying that specific AOIs retain user attention more robustly. Notably, the research has its constraints, encompassing potential deviations in webcam-based eye-tracking accuracy, the modest sample size, and post-hoc AOI categorization. As an extension, subsequent studies could probe the nuanced factors swaying dwell time within Waters' website AOIs, integrating methodologies such as the WSD thnique and proactive AOI classification.

Modeling the dissemination of privacy information in online social networks

AbstractDriven by the rapid development of information technology, online social networks (OSNs) have experienced a fast development in recent years, allowing increasingly more people to share and spread information over OSNs. The rapid rise of OSN platforms such as Facebook and Twitter is sufficient evidence of such development. As one type of information, privacy information can also be created and disseminated over an OSN, posing a severe threat to individual privacy. This article attempts to construct a model for disseminating privacy information in OSNs and to analyze the model by simulating the dissemination process of privacy information in OSNs. First, we establish network models that exhibit the main characteristics of OSNs. Second, by considering the factors related to social relationships, especially intimacy between users and the attention of users to the privacy subject, we derive the parameters for privacy information dissemination models in OSNs. Third, based on the theory of information dissemination dynamics, we construct a model for information dissemination that conforms to the properties of privacy information. We also present some experimental results based on the constructed model and analyze the characteristics of privacy information dissemination. Fourth, we study and verify the various properties of the model through a set of experiments. The proposed model provides the opportunity to better understand the dynamics of privacy information dissemination in OSNs and the effect of user behavior on dissemination.

Shifting Focus with HCEye: Exploring the Dynamics of Visual Highlighting and Cognitive Load on User Attention and Saliency Prediction

Visual highlighting can guide user attention in complex interfaces. However, its effectiveness under limited attentional capacities is underexplored. This paper examines the joint impact of visual highlighting (permanent and dynamic) and dual-task-induced cognitive load on gaze behaviour. Our analysis, using eye-movement data from 27 participants viewing 150 unique webpages reveals that while participants' ability to attend to UI elements decreases with increasing cognitive load, dynamic adaptations (i.e., highlighting) remain attention-grabbing. The presence of these factors significantly alters what people attend to and thus what is salient. Accordingly, we show that state-of-the-art saliency models increase their performance when accounting for different cognitive loads. Our empirical insights, along with our openly available dataset, enhance our understanding of attentional processes in UIs under varying cognitive (and perceptual) loads and open the door for new models that can predict user attention while multitasking.

Investigation of user-product interaction by determining the focal points of visual interest in different types of kitchen furniture: An eye-tracking study

The furniture industry faces the challenge of designing furniture that attracts greater visual attention from customers, leading to increased sales and positive impacts on the industry, businesses, economy, and the environment. In pursuit of this objective, the imperative lies in the development of user-centric designs that amplify the interaction between users and products within the furniture sector. This research aims to identify the focal points of interest in kitchen furniture through the utilization of eye-tracking technology. By analyzing the gaze points of 60 participants observing 10 different kitchen furniture models introduced in the showroom, valuable insights can be provided to designers. These insights, in turn, empower designers to fabricate products that effectively capture heightened user attention. The investigation involves the assessment of average gaze counts and the generation of visual interest heatmaps. The discernments derived from the research underscore that areas at eye level garner a more pronounced level of attention. Furthermore, the study observes that factors such as material diversity, accessory utilization, and the integration of lighting elements exert a positive influence on visual interest. The results, within the context of neurodesign, offer valuable guidance to the furniture sector. These results can support decision-making in new product design, manufacturing, and marketing, enabling the industry to produce attention-grabbing furniture.

Exploring Metaphorical Transformations of a Safety Boundary Wall in Virtual Reality.

Current virtual reality (VR) devices enable users to visually immerse themselves in the virtual world, contributing to their limited awareness of bystanders' presence. To prevent collisions when bystanders intrude into VR users' activity area, it is necessary to intuitively alert VR users to the intrusion event and the intruder's position, especially in cases where bystanders intrude from the side or behind the VR user. Existing intruder awareness cues fail to intuitively present the intrusion event in such cases. We propose a novel intruder awareness cue called "BrokenWall" by applying a metaphor of "a wall breached by invading soldiers" to the VR user's safety boundary wall. Specifically, BrokenWall refers to a safety boundary wall with a gap appearing in front of a VR user and rotating, guiding the user's attention toward an intruder coming from the side or behind the VR user. We conducted an empirical study (N = 30) comparing BrokenWall with existing awareness cue techniques, Halo and Radar. Halo employs a sphere to represent the intruder, with the size indicating proximity and the position reflecting the direction. Radar employs a radar map to visualize the intruder's position. The results showed that the BrokenWall awareness cue not only significantly reduces the time needed for users to detect an intruder but also has superior performance in subjective ratings. Based on our findings, we have established a design space for an interactive safety boundary wall to facilitate interactions between VR users and bystanders.

Study on the Sharing Behavior of Chinese Users towards Short Videos on Traditional Chinese Medicine Health in the New Media Environment

Study on the Sharing Behavior of Chinese Users towards Short Videos on Traditional Chinese Medicine Health in the New Media Environment

Experimental road safety study of the actual driver reaction to the street ads using eye tracking, multiple linear regression and decision trees methods

The article describes the results of a naturalistic driving study done in Kuwait performed by 34 participants wearing a mobile eye tracker to monitor the effect of roadside advertisements on user attention. Eye-tracking (fixations) are the main dependent variable and examined as a function of driving/roadside characteristics, particularly billboards, speed, and so forth. The results obtained were analyzed using traditional statistics (ANOVA test and multiple linear regression) and machine learning (decision tree estimation methods). From the results, it was found that road advertisements negatively affect driver attention and thus road safety. How the level of safety varies with the type and size of advertisement was also investigated. As a consequence, all of the estimates revealed that different aspects of advertising have a detrimental impact on drivers' behavior, and that the duration of fixation and the rate of acceleration before viewing an ad are impacted by advertising type and size, respectively.

Would you be impressed: applying principles of magic to chatbot conversations.

A magician's trick and a chatbot conversation have something in common: most of their audiences do not know how they work. Both are also constrained by their own limitations: magicians by the constraints of biology and physics, and dialogue systems by the status of current technology. Magicians and chatbot creators also share a goal: they want to engage their audience. But magicians, unlike the designers of dialogue systems, have centuries of practice in gracefully skirting limitations in order to engage their audience and enhance a sense of awe. In this paper, we look at these practices and identify several key principles of magic and psychology to apply to conversations between chatbots and humans. We formulate a model of communication centered on controlling the user's attention, expectations, decisions, and memory based on examples from the history of magic. We apply these magic principles to real-world conversations between humans and a social robot and evaluate their effectiveness in a Magical conversation setting compared to a Control conversation that does not incorporate magic principles. We find that human evaluators preferred interactions that incorporated magical principles over interactions that did not. In particular, magical interactions increased 1) the personalization of experience, 2) user engagement, and 3) character likability. Firstly, the magical experience was "personalized." According to survey results, the magical conversation demonstrated a statistically significant increase in "emotional connection" and "robot familiarity." Therefore, the personalization of the experience leads to higher levels of perceived impressiveness and emotional connection. Secondly, in the Magical conversation, we find that the human interlocutor is perceived to have statistically-significantly higher engagement levels in four of seven characteristics. Thirdly, participants judged the robot in the magical conversation to have a significantly greater degree of "energeticness,""humorousness," and "interestingness." Finally, evaluation of the conversations with questions intended to measure contribution of the magical principals showed statistically-significant differences for five out of nine principles, indicating a positive contribution of the magical principles to the perceived conversation experience. Overall, our evaluation demonstrates that the psychological principles underlying a magician's showmanship can be applied to the design of conversational systems to achieve more personalized, engaging, and fun interactions.

Buttery Smooth: Privacy’s Bundling with Attention in Web Browser Performance

Long considered an object of the law, Americans increasingly encounter privacy via the operations and settings of networked technologies. Based on ethnographic fieldwork with privacy engineers and their corporate colleagues, this paper examines how privacy’s manifestation in web technologies opens it to pragmatic linkages with new sensuous qualities and interpretive possibilities. The paper’s primary object is Project Quantum, a company-wide effort initiated by the Mozilla Corporation in 2016 to build a new engine for its Firefox web browser, thus radically improving Firefox’s “performance.” I show that animating Project Quantum was an ideal of smooth, snappy performance that Firefox engineers understood to be keyed to the demands of user attention and attempted to establish for users as meaningful signs of Mozilla’s engineering prowess and paternalistic care. Drawing on the study of “qualia”—phenomenal experiences of abstract qualities—I identify performance engineering as a key site of privacy’s semiotic bundling with attention, through which privacy’s practically available forms are taking on idealized qualities of speed and smoothness. Attending to privacy’s qualia, I propose, provides methodological access to the institutional and global value systems reconfiguring privacy’s political capacities as it becomes an object of technological stewardship and intervention.

Analysis of the Key Factors of User Behavior Measurement in Unexpected Events based on Feature Extraction and Selection

Artificial intelligence is important for people’s daily life. In recent years, short video platforms have risen rapidly, and TikTok APP is one of the most outstanding among them. AI tools are applied to support their big data recommendation algorithm. In the era in which everyone is using the Internet, the public can often find the reflection of all kinds of attitudes and behaviors when unexpected events occur, and this influence will inevitably become more and more important as well as draw more and more attention. Therefore, taking the key factors of the user's behavior on the TikTok platform as the research object, this thesis takes “3.21 China Eastern Airlines Passenger Plane Accident” event as the background to extend the topic. Then, the existing data of TikTok platform such as Cicada Mama is used to capture and analyze the key factors of users’ behavior in the backdrop of unexpected events, such as user attention, user influence, the heat of the event itself. Next, according to AI methods of statistics-related data, the calculation method for each factor is proposed. Finally, the analytic hierarchy process is used to establish the method of key factor measurement, to analyze the weight of each factor in the emergency.

Nature in urban green spaces: Main attractor or nice background? Drivers and dynamics of cultural ecosystem services provision

Urban parks and forests are important providers of cultural ecosystem services (CES) for the majority of the global population. Data from diverse sources are needed to reflect both ecological and social aspects of CES delivery in these areas. Understanding and disentangling this complex relationship is crucial to managing urban green spaces (UGS) in a way that maximizes users’ cultural benefits, and does not threaten the ecosystem and its functions. This paper provides a multidimensional analysis of CES delivery in parks and forests located along the urban–peri-urban axis in Warsaw, Poland. We analyzed the content of photographs posted on Instagram to identify which UGS elements attract the attention of users. We also examined whether the pattern of CES delivery was a function of the naturalness and location of the park or forest, and analyzed the factors that influence weekly and seasonal patterns of CES delivery. Although our study focused on areas where natural elements dominate, only around a quarter of photographs featured plants, water, or wild animals. Nature typically appeared as the background, while the foreground was occupied by people and their activities. Consequently, recreational services dominated over aesthetic experience; at the same time, it proved to be very difficult to identify educational services from our dataset. Air temperature, and the color of vegetation resulting from phenological changes were the most important drivers of CES delivery. We found that both the dynamics and character of CES delivery varied depending on the character of the area, and its location. Finally, delivery patterns were similar in semi-wild urban parks and outer city forests.

Animating Cartographic Meaning: Unveiling the Impact of Pictorial Symbol Motion Speed in Preattentive Processing

The primary objective of this study is to assess how the motion of dynamic point symbols impacts preattentive processing on a map. Specifically, it involves identifying the motion velocity parameters for cartographic animated pictorial symbols that contribute to the preattentive perception of the target symbols. We created five pictorial symbols, each accompanied by a unique animation tailored to convey the meaning associated with each symbol. The animation dynamics of symbols on the administrative map were distributed across arithmetic, logarithmic, and exponential scales. Eye-tracking technology was utilized to explain the user’s visual attention. The key findings reveal that, although movement does not uniformly hold the same designation in cartographic communication, it could guide user attention to identify the value peaks in quantitative map visualization. Motion velocity enhances the salience of animated symbols, making them stand out, not only against static elements but also against other animated distractors. Additionally, motion distributions between symbol classes based on exponential or arithmetic scales were identified as the most successful. Nevertheless, certain types of motion, such as rotational, do not perform well with pictorial symbols, even on the most effective motion distribution scale.

Contemporary prolepsis in digital rhetoric: the roles and functions of proleptic cues

This article explores the adaptation of Gérard Genette's concept of narrative prolepsis in the realm of social media as the proleptic technique, demonstrating its effectiveness as a tool for anticipatory rhetoric in digital communication. By analysing selected instances from Twitter and Facebook, the study illustrates how digital utterances employ proleptic cues to capture audience attention and potentially engage audiences. The concept of prolepsis, traditionally associated with narrative foresight in literature, is shown to be effectively transposed into the digital context, where it functions as a mechanism to attract user attention. This adaptation highlights the dynamism of rhetorical strategies in the evolving landscape of digital communication, underscoring the continuity of classical rhetorical principles in new media environments. Future research should incorporate a corpus study, which would allow for an in-depth examination of the diverse array of proleptic cues employed by social media influencers. Furthermore, an exploration into the persuasive efficacy of prolepsis, along with its potential links to reasoning fallacies, could provide intriguing insights. Additionally, an analysis of audience reactions to these cues could contribute to a more holistic understanding of their impact.

Évaluation de la satisfaction des professionnels de santé utilisateurs du site internet du CRAT et lancement d’une nouvelle version

In preparation for a new version of the CRAT (Centre de référence sur les agents tératogènes) website, an evaluation of user satisfaction was carried out. An invitation to complete an online questionnaire covering the various dimensions of the website (appearance, content, interactivity, ease of use, technical performance) was sent in April 2022 to healthcare professionals who referred to CRAT for clinical expertise over the previous two years. After sending out 3224 individual e-mail invitations, 758 evaluators completed the questionnaire in full (response rate: 23.5%). The evaluation revealed a high-level of overall satisfaction among site users (98.0% very satisfied or satisfied). Satisfaction with the site's appearance was also high, although comments were made about the site's lack of a modern web design. Health professionals recognized in their responses the reliable, relevant and up-to-date nature of the content of this free, public online resource, independent of the pharmaceutical industry. On the basis of these highly favorable assessments, with content that has been widely acclaimed and areas for improvement that have caught the attention of site users (evolution of its appearance, of the search tool, implementation of a mobile site), a new version of www.lecrat.fr was launched in the fall of 2023.

Headlines, Pictures, Likes: Attention to Social Media Newsfeed Post Elements on Smartphones and in Public

Scrolling through a social media newsfeed has become almost ubiquitous. Yet, it remains unknown what specific post elements people pay attention to and whether this varies depending on how they access social media newsfeeds. In an eye-tracking experiment among university students ( N = 201), we compare user attention to specific post elements like source, title, or picture, in a dynamic Facebook newsfeed by device (desktop vs. mobile) and smartphone usage environment (private vs. public). Significant attentional differences occur at the level of the newsfeed post elements. Users pay less attention to visual information on the mobile newsfeed and more attention to textual post elements in a public setting.

Green Consumer Behavior of Sports Enthusiasts on TikTok-An Analysis of the Moderating Effect of Green Concern.

The short-form video platform TikTok has become highly popular. This study explores how professional sports teams can effectively leverage short-form videos to promote green values such as environmental conservation and sustainable development, thereby capturing user attention and enhancing user engagement. This study primarily aimed to investigate the effects of a green brand image on green word of mouth (WOM), customer stickiness, and consumer purchase intention, with further examination regarding the moderating effect of green concerns on these relationships. Few studies have explored the presence of professional sports teams on TikTok, particularly in the context of green issues. Accordingly, this study adopts a novel method to develop specific and actionable recommendations for professional sports teams who have a presence on social media. Additionally, via the application of the Stimulus-Organism-Response theory, this study explains how the green brand image presented by professional sports teams on TikTok influences the interactive relationships among green WOM, customer stickiness, and consumer purchase intention. This study recruited 600 individuals who were either fans of the Taipei Fubon Braves, which is a team in Taiwan's professional basketball league P.LEAGUE+, or fans of other teams. After a confirmatory factor analysis, structural equation modeling was used to test the hypotheses. The results indicate positive correlations in all tested paths. The green concern of the Taipei Fubon Braves' fans moderated the relationship between green WOM and purchase intention; however, this moderating effect was not identified among the non-Taipei Fubon Braves fans. These findings introduce innovative concepts to the field of marketing, contributing substantially to both practical applications and academic research.

Persistence of collective memory of corporate bankruptcy events discussed on X (Twitter) is influenced by pre-bankruptcy public attention

Collective attention and memory involving significant events can be quantitatively studied via social media data. Previous studies analyzed user attention to discrete events that do not change post-event, and assume universal public attention patterns. However, dynamic events with ongoing updates are common, yielding varied individual attention patterns. We explore memory of U.S. companies filing Chapter 11 bankruptcy and being mentioned on X (formerly Twitter). Unlike discrete events, Chapter 11 entails ongoing financial changes as the company typically remains operational, influencing post-event attention dynamics. We collected 248,936 X mentions for 74 companies before and after each bankruptcy. Attention surged after bankruptcy, with distinct Low and High persistence levels compared with pre-bankruptcy attention. The two tweeting patterns were modeled using biexponential models, successfully predicting (F1-score: 0.81) post-bankruptcy attention persistence. Studying bankruptcy events on social media reveals diverse attention patterns, demonstrates how pre-bankruptcy attention affects post-bankruptcy recollection, and provides insights into memory of dynamic events.

Gaze-enabled activity recognition for augmented reality feedback

Head-mounted Augmented Reality (AR) displays overlay digital information on physical objects. Through eye tracking, they provide insights into user attention, intentions, and activities, and allow novel interaction methods based on this information. However, in physical environments, the implications of using gaze-enabled AR for human activity recognition have not been explored in detail. In an experimental study with the Microsoft HoloLens 2, we collected gaze data from 20 users while they performed three activities: Reading a text, Inspecting a device, and Searching for an object. We trained machine learning models (SVM, Random Forest, Extremely Randomized Trees) with extracted features and achieved up to 89.6% activity-recognition accuracy. Based on the recognized activity, our system—GEAR—then provides users with relevant AR feedback. Due to the sensitivity of the personal (gaze) data GEAR collects, the system further incorporates a novel solution based on the Solid specification for giving users fine-grained control over the sharing of their data. The provided code and anonymized datasets may be used to reproduce and extend our findings, and as teaching material.

Exploring factors in Human Cognition that affect Human Performance during Takeover in Autonomous Driving

Driver's mental load is an important influence on the design of the human-machine interface (HMI) for self-driving cars. During the autopilot-forced takeover process, aspects of the user's cognition, decision-making, attention, and emotional state affect the takeover performance. Therefore, the cognitive and psychological states of drivers must be considered in the HMI design of self-driving cars. And a good HMI design will reduce the user's mental burden and improve the takeover performance. In this study, a model affecting drivers' takeover performance was designed through human factors. And we refine the analysis from three aspects of cognitive load, emotional load, and environmental load by making subjective likert-style-questionnaires, derive the main influencing factors through the reliability analysis of the data, factor analysis, and other methods. This work finds that the clarity, comprehensiveness, and level of humanization of takeover messages, as well as the driver's arousal level when receiving the message, have the greatest impact on the driver's workload.

A Critical Discussion of Alert Evaluations in the Context of Continuous Glucose Monitoring System Performance.

Many continuous glucose monitoring (CGM) systems provide functionality which alerts users of potentially unwanted glycemic conditions. These alerts can include glucose threshold alerts to call the user's attention to hypoglycemia or hyperglycemia, predictive alerts warning about impeding hypoglycemia or hyperglycemia, and rate-of-change alerts. A recent review identified 129 articles about CGM performance studies, of which approximately 25% contained alert evaluations. In some studies, real alerts were assessed; however, most of these studies retrospectively determined the timing of CGM alerts because not all CGM systems record alerts which necessitates manual documentation. In contrast to assessment of real alerts, retrospective determination allows assessment of a variety of alert settings for all three types of glycemic condition alerts. Based on the literature and the Clinical and Laboratory Standards Institute's POCT05 guideline, two common approaches to threshold alert evaluation were identified, one value-based and one episode-based approach. In this review, a critical discussion of the two approaches, including a post hoc analysis of clinical study data, indicates that the episode-based approach should be preferred over the value-based approach. For predictive alerts, fewer results were found in the literature, and retrospective determination of CGM alert timing is complicated by the prediction algorithms being proprietary information. Rate-of-change alert evaluations were not reported in the identified literature, and POCT05 does not contain recommendations for assessment. A possible approach is discussed including post hoc analysis of clinical study data. To conclude, CGM systems should record alerts, and the episode-based approach to alert evaluation should be preferred.