1,720,985 research outputs found
Computer-Cognition Interfaces:Sensing and Influencing Mental Processes with Computer Interaction
No full textThe variety of information about users hidden in the details of interaction data is increasingly being utilized for recognizing complex mental processes. Digital systems can correspondingly influence mental processes of users, paving the way for new interactive systems that interface with the human mind. This thesis presents advances to such interfaces: through four papers I show how human affect and cognition can be sensed and influenced computationally.Paper 1 presents two studies that together show that affect influences mobile interaction, which allows for binary discrimination between neutral and positive affect using sensor led machine learning classification. Paper 2 builds upon the methods presented in Paper 1 and extends the classification domain to dishonesty, also using mobile interaction data. The paper shows across three studies how dishonesty and honesty vary in interactional details, and how this difference can be utilized for estimating the veracity of user behavior based on features that are engineered by mobile interaction data.Paper 3 presents a feasibility study of conducting virtual reality studies outside a laboratory, to increase heterogeneity and power. The paper shows through two studies how a range of VR tasks can be conducted without the use of an immediate experimenter, with participants carrying out experiments themselves. In Paper 4 I apply this methodology, and conduct a VR study with more than 200 participants to study how manipulations to avatars can influence affect responses. The paper presents evidence supporting the link between affect and avatars, and additionally discusses the interplay between positive affect and body ownership.<br/
Demand characteristics in human–computer experiments
No full textDemand characteristics refer to cues that can inform participants in experiments about the hypothesis and influence their behavior. They lead researchers to erroneously infer non-existing effects, undermining the experimental integrity of empirical studies. Despite a widespread acknowledgment of their confounding influence in experimental psychology, experiments involving humans and computers to a lesser extent consider effects of demand characteristics, as computerized protocols are thought to be immune to some experimenter biases. Furthermore, demand characteristics are considered to mainly effect subjective measures. As a result, demand characteristics often remain uncontrolled in studies involving computers, and in particular for objective measures such as performance. In this paper, we present two experiments that underline the importance of demand characteristics in human–computer interaction experiments. In a text-entry study, we made participants believe they were evaluating a research-based keyboard. This belief led to increased performance and self-reported user experience. In a second study, we conducted a thought experiment on the illusion of body ownership in virtual reality, where the experimental design indicated the study hypothesis. We found hypothesis-compliant responses from participants, even when they did not experience the illusion. We conclude that demand characteristics pose a significant challenge to the interpretation and validity of human–computer experiments, even when they are fully automated. We discuss the implications and offer guidelines to mitigate effects of demand characteristics.</p
Hafnia Hands: A Multi-Skin Hand Texture Resource for Virtual Reality Research
Get PDFWe created a hand texture resource (with different skin tone versions as well as non-human hands) for use in virtual reality studies. This makes it easier to run lab and remote studies where the hand representation is matched to the participants’ own skin tone. We validate that the virtual hands with our textures align with participants’ view of their own real hands and allow to create VR applications where participants have an increased sense of body ownership. These properties are critical for a range of VR studies, such as of immersion.<br/
Why Do People Take Screenshots on Their Smartphones?
No full textScreenshots are ubiquitous in mobile computing, yet poorly understood. This paper advances our understanding of reasons for capturing, storing, and sharing screenshots. A crowdsourced user study was conducted where 52 participants shared personal screenshots from their phones, alongside textual reasons for why they were captured. Using mixed methods analyses we uncover common and uncommon screenshot practices that have not previously been documented. By analyzing the language used to describe reasons for taking screenshots, we document a variety of motivations for screenshot captures that provide opportunities for design. We furthermore report nine overarching themes in contemporary mobile screenshot use, considerably extending the currently held view of screenshots as a type of social computing. To inform design, we propose novel screenshot-centered interaction concepts that bridge the empirical findings. Last, we position screenshotting as a style of mobile interaction, which we argue is an undeveloped opportunity for advancing interactivity for mobile computing.Screenshots are ubiquitous in mobile computing, yet poorly understood. This paper advances our understanding of reasons for capturing, storing, and sharing screenshots. A crowdsourced user study was conducted where 52 participants shared personal screenshots from their phones, alongside textual reasons for why they were captured. Using mixed methods analyses we uncover common and uncommon screenshot practices that have not previously been documented. By analyzing the language used to describe reasons for taking screenshots, we document a variety of motivations for screenshot captures that provide opportunities for design. We furthermore report nine overarching themes in contemporary mobile screenshot use, considerably extending the currently held view of screenshots as a type of social computing. To inform design, we propose novel screenshot-centered interaction concepts that bridge the empirical findings. Last, we position screenshotting as a style of mobile interaction, which we argue is an undeveloped opportunity for advancing interactivity for mobile computing
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
A Systematic Review and Meta-analysis of Text Entry Studies
No full textText entry is a notably standardized research field in human-computer interaction, with established benchmarks and methodologies enabling rigorous comparisons across studies. Nevertheless, meta research in text-entry is scarce. This meta-analysis summarizes findings and effects from text entry experiments published from 1990 to 2024. Our records show that most text-entry experiments feature a baseline and an experimental UI, and that they mostly show that the experimental UI is superior (), with regards to text entry speed. We found that earlier text entry research focused mostly on the development of novel techniques, whereas recent text entry research, to a larger extent, adapts existing input methods to new devices, such as smartwatches or virtual reality headsets. We also find that text entry research often lacks statistical power (, ), relies on small sample sizes (), and is mostly conducted with within-subjects designs (84. Subjective evaluations of text entry systems beyond objective performance are rare. Our analysis found evidence for systematic publication bias in text entry research, as indicated by funnel plot asymmetry and a significant weight-function model adjustment. This underlines the research field's competitive culture of publishing research only if entry speed is beaten in comparison to some baseline.Text entry is a notably standardized research field in human-computer interaction, with established benchmarks and methodologies enabling rigorous comparisons across studies. Nevertheless, meta research in text-entry is scarce. This meta-analysis summarizes findings and effects from text entry experiments published from 1990 to 2024. Our records show that most text-entry experiments feature a baseline and an experimental UI, and that they mostly show that the experimental UI is superior (g = 1.68), with regards to text entry speed. We found that earlier text entry research focused mostly on the development of novel techniques, whereas recent text entry research, to a larger extent, adapts existing input methods to new devices, such as smartwatches or virtual reality headsets. We also find that text entry research often lacks statistical power (M = 0.66, SD = 0.37), relies on small sample sizes (Mdn = 12), and is mostly conducted with within-subjects designs (84%). Subjective evaluations of text entry systems beyond objective performance are rare. Our analysis found evidence for systematic publication bias in text entry research, as indicated by funnel plot asymmetry and a significant weight-function model adjustment. This underlines the research field’s competitive culture of publishing research only if entry speed is beaten in comparison to some baseline
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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