Information Visualization最新文献_第2页

ProtoExplorer: Interpretable forensic analysis of deepfake videos using prototype exploration and refinement ProtoExplorer：利用原型探索和改进对深度伪造视频进行可解释的取证分析

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2024-04-17 DOI: 10.1177/14738716241238476

Merel de Leeuw den Bouter, Javier Lloret Pardo, Zeno Geradts, Marcel Worring

{"title":"ProtoExplorer: Interpretable forensic analysis of deepfake videos using prototype exploration and refinement","authors":"Merel de Leeuw den Bouter, Javier Lloret Pardo, Zeno Geradts, Marcel Worring","doi":"10.1177/14738716241238476","DOIUrl":"https://doi.org/10.1177/14738716241238476","url":null,"abstract":"In high-stakes settings, Machine Learning models that can provide predictions that are interpretable for humans are crucial. This is even more true with the advent of complex deep learning based models with a huge number of tunable parameters. Recently, prototype-based methods have emerged as a promising approach to make deep learning interpretable. We particularly focus on the analysis of deepfake videos in a forensics context. Although prototype-based methods have been introduced for the detection of deepfake videos, their use in real-world scenarios still presents major challenges, in that prototypes tend to be overly similar and interpretability varies between prototypes. This paper proposes a Visual Analytics process model for prototype learning, and, based on this, presents ProtoExplorer, a Visual Analytics system for the exploration and refinement of prototype-based deepfake detection models. ProtoExplorer offers tools for visualizing and temporally filtering prototype-based predictions when working with video data. It disentangles the complexity of working with spatio-temporal prototypes, facilitating their visualization. It further enables the refinement of models by interactively deleting and replacing prototypes with the aim to achieve more interpretable and less biased predictions while preserving detection accuracy. The system was designed with forensic experts and evaluated in a number of rounds based on both open-ended think aloud evaluation and interviews. These sessions have confirmed the strength of our prototype-based exploration of deepfake videos while they provided the feedback needed to continuously improve the system.","PeriodicalId":50360,"journal":{"name":"Information Visualization","volume":"183 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140612431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing graph drawings through edge bundling using clustering ensembles 利用聚类组合通过边缘捆绑增强图形绘制能力

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2024-04-08 DOI: 10.1177/14738716241239619

Raissa dos Santos Vieira, Hugo Alexandre Dantas do Nascimento, Joelma de Moura Ferreira, Les Foulds

引用次数: 0

Towards an understanding and explanation for mixed-initiative artificial scientific text detection 理解和解释混合倡议人工科学文本检测

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2024-04-08 DOI: 10.1177/14738716241240156

Luoxuan Weng, Shi Liu, Hang Zhu, Jiashun Sun, Wong Kam-Kwai, Dongming Han, Minfeng Zhu, Wei Chen

{"title":"Towards an understanding and explanation for mixed-initiative artificial scientific text detection","authors":"Luoxuan Weng, Shi Liu, Hang Zhu, Jiashun Sun, Wong Kam-Kwai, Dongming Han, Minfeng Zhu, Wei Chen","doi":"10.1177/14738716241240156","DOIUrl":"https://doi.org/10.1177/14738716241240156","url":null,"abstract":"Large language models (LLMs) have gained popularity in various fields for their exceptional capability of generating human-like text. Their potential misuse has raised social concerns about plagiarism in academic contexts. However, effective artificial scientific text detection is a non-trivial task due to several challenges, including (1) the lack of a clear understanding of the differences between machine-generated and human-written scientific text, (2) the poor generalization performance of existing methods caused by out-of-distribution issues, and (3) the limited support for human-machine collaboration with sufficient interpretability during the detection process. In this paper, we first identify the critical distinctions between machine-generated and human-written scientific text through a quantitative experiment. Then, we propose a mixed-initiative workflow that combines human experts’ prior knowledge with machine intelligence, along with a visual analytics system to facilitate efficient and trustworthy scientific text detection. Finally, we demonstrate the effectiveness of our approach through two case studies and a controlled user study. We also provide design implications for interactive artificial text detection tools in high-stakes decision-making scenarios.","PeriodicalId":50360,"journal":{"name":"Information Visualization","volume":"1 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140586471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Principal trade-off analysis 主要权衡分析

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2024-04-05 DOI: 10.1177/14738716241239018

Alexander Strang, David Sewell, Alexander Kim, Kevin Alcedo, David Rosenbluth

{"title":"Principal trade-off analysis","authors":"Alexander Strang, David Sewell, Alexander Kim, Kevin Alcedo, David Rosenbluth","doi":"10.1177/14738716241239018","DOIUrl":"https://doi.org/10.1177/14738716241239018","url":null,"abstract":"How are the advantage relations between a set of agents playing a game organized and how do they reflect the structure of the game? In this paper, we illustrate ‘Principal Trade-off Analysis’ (PTA), a decomposition method that embeds games into a low-dimensional feature space. We argue that the embeddings are more revealing than previously demonstrated by developing an analogy to Principal Component Analysis (PCA). PTA represents an arbitrary two-player zero-sum game as linear combination of simple games via the projection of policy profiles into orthogonal 2D feature planes. We show that the feature planes represent unique strategic trade-offs and truncation of the sequence provides insightful model reduction and visualization. We demonstrate the validity of PTA on a quartet of games (Kuhn poker, RPS + 2, Blotto and Pokemon). In Kuhn poker, PTA clearly identifies the trade-off between bluffing and calling. In Blotto, PTA identifies game symmetries and specifies strategic trade-offs associated with distinct win conditions. These symmetries reveal limitations of PTA unaddressed in previous work. For Pokemon, PTA recovers clusters that naturally correspond to Pokemon types, correctly identifies the designed trade-off between those types, and discovers a rock-paper-scissor (RPS) cycle in the Pokemon generation type – all absent any specific information except game outcomes.","PeriodicalId":50360,"journal":{"name":"Information Visualization","volume":"48 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140586479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

From word clouds to Word Rain: Revisiting the classic word cloud to visualize climate change texts 从文字云到文字雨：重温经典词云，将气候变化文本可视化

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2024-03-28 DOI: 10.1177/14738716241236188

Maria Skeppstedt, Magnus Ahltorp, Kostiantyn Kucher, Matts Lindström

引用次数: 0

An empirical study of counterfactual visualization to support visual causal inference 支持可视化因果推理的反事实可视化实证研究

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2024-02-07 DOI: 10.1177/14738716241229437

Arran Zeyu Wang, David Borland, David Gotz

引用次数: 0

ClustML: A measure of cluster pattern complexity in scatterplots learnt from human-labeled groupings ClustML：从人类标记的分组中学习散点图中聚类模式复杂性的测量方法

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2024-01-30 DOI: 10.1177/14738716231220536

Mostafa M Hamza, Ehsan Ullah, Abdelkader Baggag, Halima Bensmail, Michael Sedlmair, Michael Aupetit

引用次数: 0

Interact: A visual what-if analysis tool for virtual product design Interact：用于虚拟产品设计的可视化假设分析工具

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2023-12-29 DOI: 10.1177/14738716231216030

V. Ciorna, Guy Melançon, F. Petry, Mohammad Ghoniem

{"title":"Interact: A visual what-if analysis tool for virtual product design","authors":"V. Ciorna, Guy Melançon, F. Petry, Mohammad Ghoniem","doi":"10.1177/14738716231216030","DOIUrl":"https://doi.org/10.1177/14738716231216030","url":null,"abstract":"Virtual prototyping is increasingly used by businesses to streamline operations, cut costs, and enhance daily operations. This often includes a variety of modeling techniques among which, complex, black-box models. The path from model development to utilization in applied contexts is yet long. Domain experts need to be convinced of the validity of the models and to trust their predictions. To be used in the field, model capabilities need to be affordable, that is, allow rapid and interactive scenario building, even for non-experts. Complex relations governed by statistical interactions must be unveiled for users to understand unexpected predictions. We propose Interact, a model-agnostic, visual what-if tool for regression problems, supporting (1) the visualization of statistical interactions between features, (2) the creation of interactive what-if scenarios using predictive models, (3) the evaluation of model quality and building trust, and (4) the externalization of knowledge through model explainability. While the approach applies in various industrial contexts, we validate the application purpose and design with a detailed case study and a qualitative user study with engineers in the tire industry. By unraveling statistical interactions between features, the INTERACT tool proves to be useful to increase the transparency of black-box machine learning models. We also reflect on lessons learned concerning the development of visual what-if tools for virtual product development and beyond.","PeriodicalId":50360,"journal":{"name":"Information Visualization","volume":" 31","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139143626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Strategies for evaluating visual analytics systems: A systematic review and new perspectives 评估视觉分析系统的策略：系统回顾与新视角

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2023-12-28 DOI: 10.1177/14738716231212568

Md. Rafiqul Islam, Shanjita Akter, Linta Islam, Imran Razzak, Xianzhi Wang, Guandong Xu

{"title":"Strategies for evaluating visual analytics systems: A systematic review and new perspectives","authors":"Md. Rafiqul Islam, Shanjita Akter, Linta Islam, Imran Razzak, Xianzhi Wang, Guandong Xu","doi":"10.1177/14738716231212568","DOIUrl":"https://doi.org/10.1177/14738716231212568","url":null,"abstract":"In recent times, visual analytics systems (VAS) have been used to solve various complex issues in diverse application domains. Nonetheless, an inherent drawback arises from the insufficient evaluation of VAS, resulting in occasional inaccuracies when it comes to analytical reasoning, information synthesis, and deriving insights from vast, ever-changing, ambiguous, and frequently contradictory data. Hence, the significance of implementing an appropriate evaluation methodology cannot be overstated, as it plays a pivotal role in enhancing the design and development of visualization systems. This paper assesses visualization systems by providing a systematic exploration of various evaluation strategies (ES). While several existing studies have examined some ES, the extent of comprehensive and systematic review for visualization research remains limited. In this work, we introduce seven state-of-the-art and widely recognized ES namely (1) dashboard comparison; (2) insight-based evaluation; (3) log data analysis; (4) Likert scales; (5) qualitative and quantitative analysis; (6) Nielsen’s heuristics; and (7) eye trackers. Moreover, it delves into their historical context and explores numerous applications where these ES have been employed, shedding light on the associated evaluation practices. Through our comprehensive review, we overview and analyze the predominant evaluation goals within the visualization community, elucidating their evolution and the inherent contrasts. Additionally, we identify the open challenges that arise with the emergence of new ES, while also highlighting the key themes gleaned from the existing literature that hold potential for further exploration in future studies.","PeriodicalId":50360,"journal":{"name":"Information Visualization","volume":"27 s1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139150051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Studying the resiliency of the anchoring bias to locus of control in visualization 研究可视化中锚定偏差对控制定位的适应能力

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2023-11-24 DOI: 10.1177/14738716231213987

Tomás Alves, Ricardo Velhinho, J. Henriques-Calado, Daniel Gonçalves, S. Gama

{"title":"Studying the resiliency of the anchoring bias to locus of control in visualization","authors":"Tomás Alves, Ricardo Velhinho, J. Henriques-Calado, Daniel Gonçalves, S. Gama","doi":"10.1177/14738716231213987","DOIUrl":"https://doi.org/10.1177/14738716231213987","url":null,"abstract":"The anchoring effect is the over-reliance on an initial piece of information when making decisions. It is one of the most pervasive and robust biases. Recently, literature has focused on knowing how influential the anchoring effect is when applied to information visualization, with studies finding its reproducibility in the field. Despite the extensive literature surrounding the anchoring effect’s robustness, there is still a need for research on which individual differences make people more susceptible. We explore how Locus of Control influences visualization’s ubiquitous and resilient anchoring effect. Locus of Control differentiates individuals who believe their life depends on their behavior or actions from those who blame outside factors such as destiny or luck for their life’s outcomes. We focus on the relationship between Locus of Control and the anchoring effect by exposing subjects to an anchor and analyzing their interaction with a complex visualization. Our results show that the anchoring strategies primed individuals and suggest that the Locus of Control plays a role in the susceptibility to the anchoring effect.","PeriodicalId":50360,"journal":{"name":"Information Visualization","volume":"32 10","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139240023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0