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Few concepts are as ubiquitous in computational fields as trust. However, in the case of information visualization, there are several unique and complex challenges, chief among them: defining and measuring trust. In this paper, we…

人机交互 · 计算机科学 2023-08-10 Saugat Pandey , Oen G. McKinley , R. Jordan Crouser , Alvitta Ottley

Despite the importance of viewers' trust in data visualization, there is a lack of research on the viewers' own perspective on their trust. In addition, much of the research on trust remains relatively theoretical and inaccessible for…

人机交互 · 计算机科学 2025-03-17 Oen McKinley , Saugat Pandey , Alvitta Ottley

Trust is an essential aspect of data visualization, as it plays a crucial role in the interpretation and decision-making processes of users. While research in social sciences outlines the multi-dimensional factors that can play a role in…

人机交互 · 计算机科学 2023-10-02 Hamza Elhamdadi , Adam Stefkovics , Johanna Beyer , Eric Moerth , Cindy Xiong Bearfield , Carolina Nobre

Trust plays a critical role in visual data communication and decision-making, yet existing visualization research employs varied trust measures, making it challenging to compare and synthesize findings across studies. In this work, we first…

Trust is fundamental to effective visual data communication between the visualization designer and the reader. Although personal experience and preference influence readers' trust in visualizations, visualization designers can leverage…

人机交互 · 计算机科学 2022-09-29 Hamza Elhamdadi , Aimen Gaba , Yea-Seul Kim , Cindy Xiong

Emotion is an important factor to consider when designing visualizations as it can impact the amount of trust viewers place in a visualization, how well they can retrieve information and understand the underlying data, and how much they…

人机交互 · 计算机科学 2024-07-29 Carter Blair , Xiyao Wang , Charles Perin

User trust is a crucial consideration in designing robust visual analytics systems that can guide users to reasonably sound conclusions despite inevitable biases and other uncertainties introduced by the human, the machine, and the data…

人机交互 · 计算机科学 2022-09-12 Joshua Boley , Maoyuan Sun

Defining trust is an important endeavor given its applicability to assessing public mood to much of the innovation in the newly formed autonomous industry, such as artificial intelligence (AI),medical bots, drones, autonomous vehicles, and…

人工智能 · 计算机科学 2020-09-29 Rita Borgo , Darren J Edwards

Interface design can directly influence trustworthiness of a software. Thereby, it affects users' intention to use a tool. Previous research on user trust has not comprehensively addressed user interface design, though. We lack an…

人机交互 · 计算机科学 2022-03-01 Valentin Zieglmeier , Antonia Maria Lehene

Journalists and visualization designers include visualizations in their articles and storytelling tools to deliver their message effectively. But design decisions they make to represent information, such as the graphical dimensions they…

人机交互 · 计算机科学 2023-06-01 Hayeong Song , John Stasko

Spatial analysis can generate both exogenous and endogenous biases, which will lead to ethics issues. Exogenous biases arise from external factors or environments and are unrelated to internal operating mechanisms, while endogenous biases…

人机交互 · 计算机科学 2024-12-20 Chuan Chen , Peng Luo , Bo Zhao , Yu Feng , Liqiu Meng

Trust has been shown to be a key factor in effective human-robot collaboration. In the context of assistive robotics, the effect of trust factors on human experience is further pronounced. Personalization of assistive robots is an…

机器人学 · 计算机科学 2023-10-31 Parv Kapoor , Simon Chu , Angela Chen

Explanations are central to improving transparency, trust, and user satisfaction in recommender systems (RS), yet it remains unclear how different explanation formats (visual vs. textual) are suited to users with different personal…

Systems relying on ML have become ubiquitous, but so has biased behavior within them. Research shows that bias significantly affects stakeholders' trust in systems and how they use them. Further, stakeholders of different backgrounds view…

人机交互 · 计算机科学 2025-08-04 Zhanna Kaufman , Madeline Endres , Cindy Xiong Bearfield , Yuriy Brun

Interpersonal trust is recognized as one of the pillars of collaboration and successful learning among students in virtual learning environments (VLEs). This systematic mapping study investigates attributes, phases, and features that…

计算机与社会 · 计算机科学 2025-10-28 Marcelo Pereira Barbosa , Rita Suzana Pitangueira Maciel

Data visualizations are increasingly seen as socially constructed, with several recent studies positing that perceptions and interpretations of visualization artifacts are shaped through complex sets of interactions between members of a…

人机交互 · 计算机科学 2025-02-17 Priya Dhawka , Sayamindu Dasgupta

Machine learning technology has become ubiquitous, but, unfortunately, often exhibits bias. As a consequence, disparate stakeholders need to interact with and make informed decisions about using machine learning models in everyday systems.…

人机交互 · 计算机科学 2024-01-12 Aimen Gaba , Zhanna Kaufman , Jason Chueng , Marie Shvakel , Kyle Wm. Hall , Yuriy Brun , Cindy Xiong Bearfield

In contrast to objectively measurable aspects (such as accuracy, reading speed, or memorability), the subjective experience of visualizations has only recently gained importance, and we have less experience how to measure it. We explore how…

人机交互 · 计算机科学 2023-10-24 Laura Koesten , Drew Dimmery , Michael Gleicher , Torsten Möller

This study aims to explore the associations between individuals' trust dynamics in automated/autonomous technologies and their personal characteristics, and to further examine whether personal characteristics can be used to predict a user's…

人机交互 · 计算机科学 2025-06-16 Hyesun Chung , X. Jessie Yang

Developments in data visualization research have enabled visualization systems to achieve great general usability and application across a variety of domains. These advancements have improved not only people's understanding of data, but…

人机交互 · 计算机科学 2020-05-21 Zhengliang Liu , R. Jordan Crouser , Alvitta Ottley
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