Eric D. Ragan
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View article: A Systematic Survey of Empirical User Studies of Unintentional Information Disclosure in Everyday Digital Interaction
A Systematic Survey of Empirical User Studies of Unintentional Information Disclosure in Everyday Digital Interaction Open
The exchange of personal information in digital environments poses significant risks, including identity theft, privacy breaches, and data misuse. Addressing these challenges requires a deep understanding of user behavior and mental models…
View article: Privacy-by-design: Case studies in interactive record linkage using a hybrid human-computer system
Privacy-by-design: Case studies in interactive record linkage using a hybrid human-computer system Open
On-demand access and masking techniques along with risk quantification through a hybrid human-computer system can significantly reduce disclosure while still minimizing false positives and false negatives in real-world RL.
View article: User Profiling in Human-AI Design: An Empirical Case Study of Anchoring Bias, Individual Differences, and AI Attitudes
User Profiling in Human-AI Design: An Empirical Case Study of Anchoring Bias, Individual Differences, and AI Attitudes Open
People form perceptions and interpretations of AI through external sources prior to their interaction with new technology. For example, shared anecdotes and media stories influence prior beliefs that may or may not accurately represent the…
View article: Empirical Insights into Analytic Provenance Summarization: A Study on Segmenting Data Analysis Workflows
Empirical Insights into Analytic Provenance Summarization: A Study on Segmenting Data Analysis Workflows Open
The complexity of exploratory data analysis poses significant challenges for collaboration and effective communication of analytic workflows. Automated methods can alleviate these challenges by summarizing workflows into more interpretable…
View article: From Data Dump to Digestible Chunks: Automated Segmentation and Summarization of Provenance Logs for Communication
From Data Dump to Digestible Chunks: Automated Segmentation and Summarization of Provenance Logs for Communication Open
Communicating one's sensemaking during a complex analysis session to explain thought processes is hard, yet most intelligence occurs in collaborative settings. Team members require a deeper understanding of the work being completed by thei…
View article: Expanding the Ontology of Organizational Structures of Trauma Centers and Trauma Systems.
Expanding the Ontology of Organizational Structures of Trauma Centers and Trauma Systems. Open
A knowledge gap exists regarding the impact of organizational parameters of trauma centers and patient outcomes. This is partially due to such organizational parameters being understudied. The Ontology of Organizational Structures of Traum…
View article: CaptainCook4D: A Dataset for Understanding Errors in Procedural Activities
CaptainCook4D: A Dataset for Understanding Errors in Procedural Activities Open
Following step-by-step procedures is an essential component of various activities carried out by individuals in their daily lives. These procedures serve as a guiding framework that helps to achieve goals efficiently, whether it is assembl…
View article: Explainable Activity Recognition in Videos using Deep Learning and Tractable Probabilistic Models
Explainable Activity Recognition in Videos using Deep Learning and Tractable Probabilistic Models Open
We consider the following video activity recognition (VAR) task: given a video, infer the set of activities being performed in the video and assign each frame to an activity. Although VAR can be solved accurately using existing deep learni…
View article: Preliminary Perspectives on Information Passing in the Intelligence Community
Preliminary Perspectives on Information Passing in the Intelligence Community Open
Analyst sensemaking research typically focuses on individual or small groups conducting intelligence tasks. This has helped understand information retrieval tasks and how people communicate information. As a part of the grand challenge of …
View article: StoryFacets: A design study on storytelling with visualizations for collaborative data analysis
StoryFacets: A design study on storytelling with visualizations for collaborative data analysis Open
Tracking the sensemaking process is a well-established practice in many data analysis tools, and many visualization tools facilitate overview and recall during and after exploration. However, the resulting communication materials such as p…
View article: The Influence of Visual Provenance Representations on Strategies in a Collaborative Hand-off Data Analysis Scenario
The Influence of Visual Provenance Representations on Strategies in a Collaborative Hand-off Data Analysis Scenario Open
Conducting data analysis tasks rarely occur in isolation. Especially in intelligence analysis scenarios where different experts contribute knowledge to a shared understanding, members must communicate how insights develop to establish comm…
View article: A Modified Tactile Brush Algorithm for Complex Touch Gestures
A Modified Tactile Brush Algorithm for Complex Touch Gestures Open
Several researchers have investigated phantom tactile sensation (i.e., the perception of a nonexistent actuator between two real actuators) and apparent tactile motion (i.e., the perception of a moving actuator due to time delays between o…
View article: An Empirical Study on the Relationship Between the Number of Coordinated Views and Visual Analysis
An Empirical Study on the Relationship Between the Number of Coordinated Views and Visual Analysis Open
Coordinated Multiple views (CMVs) are a visualization technique that simultaneously presents multiple visualizations in separate but linked views. There are many studies that report the advantages (e.g., usefulness for finding hidden relat…
View article: Developing and Testing Software for Linking Patient Data from Multiple Sources
Developing and Testing Software for Linking Patient Data from Multiple Sources Open
Background: Comparative effectiveness research (CER) and patient-centered outcomes research (PCOR) routinely use secondary data (eg, insurance claims, health records). Leveraging secondary data requires effective and accurate record linkag…
View article: The Influence of Visual Provenance Representations on Strategies in a Collaborative Hand-off Data Analysis Scenario
The Influence of Visual Provenance Representations on Strategies in a Collaborative Hand-off Data Analysis Scenario Open
Conducting data analysis tasks rarely occur in isolation. Especially in intelligence analysis scenarios where different experts contribute knowledge to a shared understanding, members must communicate how insights develop to establish comm…
View article: Explainable activity recognition in videos: Lessons learned
Explainable activity recognition in videos: Lessons learned Open
We consider the following activity recognition task: given a video, infer the set of activities being performed in the video and assign each frame to an activity. This task can be solved using modern deep learning architectures based on ne…
View article: How level of explanation detail affects human performance in interpretable intelligent systems: A study on explainable fact checking
How level of explanation detail affects human performance in interpretable intelligent systems: A study on explainable fact checking Open
Explainable artificial intelligence (XAI) systems aim to provide users with information to help them better understand computational models and reason about why outputs were generated. However, there are many different ways an XAI interfac…
View article: A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems
A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems Open
The need for interpretable and accountable intelligent systems grows along with the prevalence of artificial intelligence ( AI ) applications used in everyday life. Explainable AI ( XAI ) systems are intended to self-explain the reasoning …
View article: Machine Learning Explanations to Prevent Overtrust in Fake News Detection
Machine Learning Explanations to Prevent Overtrust in Fake News Detection Open
Combating fake news and misinformation propagation is a challenging task in the post-truth era. News feed and search algorithms could potentially lead to unintentional large-scale propagation of false and fabricated information with users …
View article: Identifying and prioritizing benefits and risks of using privacy-enhancing software through participatory design: a nominal group technique study with patients living with chronic conditions
Identifying and prioritizing benefits and risks of using privacy-enhancing software through participatory design: a nominal group technique study with patients living with chronic conditions Open
Objective While patients often contribute data for research, they want researchers to protect their data. As part of a participatory design of privacy-enhancing software, this study explored patients’ perceptions of privacy protection in r…
View article: Micro-entries: Encouraging Deeper Evaluation of Mental Models Over Time for Interactive Data Systems
Micro-entries: Encouraging Deeper Evaluation of Mental Models Over Time for Interactive Data Systems Open
Many interactive data systems combine visual representations of data with embedded algorithmic support for automation and data exploration. To effectively support transparent and explainable data systems, it is important for researchers an…
View article: The Role of Domain Expertise in User Trust and the Impact of First Impressions with Intelligent Systems
The Role of Domain Expertise in User Trust and the Impact of First Impressions with Intelligent Systems Open
Domain-specific intelligent systems are meant to help system users in their decision-making process. Many systems aim to simultaneously support different users with varying levels of domain expertise, but prior domain knowledge can affect …
View article: Soliciting Human-in-the-Loop User Feedback for Interactive Machine Learning Reduces User Trust and Impressions of Model Accuracy
Soliciting Human-in-the-Loop User Feedback for Interactive Machine Learning Reduces User Trust and Impressions of Model Accuracy Open
Mixed-initiative systems allow users to interactively provide feedback to potentially improve system performance. Human feedback can correct model errors and update model parameters to dynamically adapt to changing data. Additionally, many…
View article: Empirical Study of Focus-Plus-Context and Aggregation Techniques for the Visualization of Streaming Data
Empirical Study of Focus-Plus-Context and Aggregation Techniques for the Visualization of Streaming Data Open
Analysis of streaming data often involves both real-time monitoring of incoming data as well as contextual awareness of data history. A focus-plus-context approach can support both goals, with variable levels of visual aggregation making i…
View article: Preserving Contextual Awareness during Selection of Moving Targets in Animated Stream Visualizations
Preserving Contextual Awareness during Selection of Moving Targets in Animated Stream Visualizations Open
In many types of dynamic interactive visualizations, it is often desired to interact with moving objects. Stopping moving objects can make selection easier, but pausing animated content can disrupt perception and understanding of the visua…
View article: The Role of Domain Expertise in User Trust and the Impact of First\n Impressions with Intelligent Systems
The Role of Domain Expertise in User Trust and the Impact of First\n Impressions with Intelligent Systems Open
Domain-specific intelligent systems are meant to help system users in their\ndecision-making process. Many systems aim to simultaneously support different\nusers with varying levels of domain expertise, but prior domain knowledge can\naffe…
View article: Machine Learning Explanations to Prevent Overtrust in Fake News\n Detection
Machine Learning Explanations to Prevent Overtrust in Fake News\n Detection Open
Combating fake news and misinformation propagation is a challenging task in\nthe post-truth era. News feed and search algorithms could potentially lead to\nunintentional large-scale propagation of false and fabricated information with\nuse…
View article: Weight 20Newsgroup words.
Weight 20Newsgroup words. Open
Subset of the data used in "Quantitative Evaluation of Machine Learning Explanations: A Human-Grounded Benchmark". Contains words from documents in the 20Newsgroup dataset, which were weighted based on annotators' selection for each text a…
View article: Weight 20Newsgroup words.
Weight 20Newsgroup words. Open
Subset of the data used in "Quantitative Evaluation of Machine Learning Explanations: A Human-Grounded Benchmark". Contains words from documents in the 20Newsgroup dataset, which were weighted based on annotators' selection for each text a…