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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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 exploration system to effectively analyze the visual metaphor used in sentiment visualization 有效分析情感可视化中使用的视觉隐喻的探索系统

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2024-02-15 DOI: 10.1177/14738716241228593

Hyoji Ha, Kwang-jin Moon, Hye-Gyoung Joung, Hyegyeong Kim, Kyungwon Lee

{"title":"An exploration system to effectively analyze the visual metaphor used in sentiment visualization","authors":"Hyoji Ha, Kwang-jin Moon, Hye-Gyoung Joung, Hyegyeong Kim, Kyungwon Lee","doi":"10.1177/14738716241228593","DOIUrl":"https://doi.org/10.1177/14738716241228593","url":null,"abstract":"In the field of data visualization, there has been a recent trend of using a complex type of visualization with a multidimensional structure or using several visualizations in parallel when summarizing the results of sentiment analysis. Although this trend may be useful for sophisticated sentiment analysis, such analysis is difficult for the general public and novice researchers. To address this issue, there has recently been a trend of visualizing sentiments using visual metaphors. To facilitate the understanding of related cases, it is necessary to have a systematic means of grasping the sentiment target, the purpose and motivation of research, and the representations used as substitutes for visual metaphors. Therefore, the objective of the present study was to develop an exploration system that can analyze the visual metaphors used in the case of sentiment visualization. For this study, (1) sentiment visualization cases in which visual metaphors are used were collected. (2) After a taxonomy composed of the categories of “target, intermediation, representation, visual variable, and visualization technique” was constructed, it was used to analyze sentences of visual metaphors appearing in sentiment visualization cases. (3) An exploration system capable of grasping the semantic relationships of sub-elements within the five categories of the taxonomy and intuitively interpreting visual metaphors was developed so that appropriate cases can be recommended to sentiment visualization researchers. (4) The approach and usefulness of the exploration system were explained using user scenarios. (5) A case study was conducted to show that the provided system can be analyzed from various perspectives. (6) The usability of the exploration system was demonstrated through a verification targeting experts. The proposed system allows researchers and analysts to intuitively grasp “what types of visual metaphor method and idea should be equipped to visualize sentiment data in an easier way to understand.”","PeriodicalId":50360,"journal":{"name":"Information Visualization","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139833949","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

An exploration system to effectively analyze the visual metaphor used in sentiment visualization 有效分析情感可视化中使用的视觉隐喻的探索系统

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2024-02-15 DOI: 10.1177/14738716241228593

Hyoji Ha, Kwang-jin Moon, Hye-Gyoung Joung, Hyegyeong Kim, Kyungwon Lee

{"title":"An exploration system to effectively analyze the visual metaphor used in sentiment visualization","authors":"Hyoji Ha, Kwang-jin Moon, Hye-Gyoung Joung, Hyegyeong Kim, Kyungwon Lee","doi":"10.1177/14738716241228593","DOIUrl":"https://doi.org/10.1177/14738716241228593","url":null,"abstract":"In the field of data visualization, there has been a recent trend of using a complex type of visualization with a multidimensional structure or using several visualizations in parallel when summarizing the results of sentiment analysis. Although this trend may be useful for sophisticated sentiment analysis, such analysis is difficult for the general public and novice researchers. To address this issue, there has recently been a trend of visualizing sentiments using visual metaphors. To facilitate the understanding of related cases, it is necessary to have a systematic means of grasping the sentiment target, the purpose and motivation of research, and the representations used as substitutes for visual metaphors. Therefore, the objective of the present study was to develop an exploration system that can analyze the visual metaphors used in the case of sentiment visualization. For this study, (1) sentiment visualization cases in which visual metaphors are used were collected. (2) After a taxonomy composed of the categories of “target, intermediation, representation, visual variable, and visualization technique” was constructed, it was used to analyze sentences of visual metaphors appearing in sentiment visualization cases. (3) An exploration system capable of grasping the semantic relationships of sub-elements within the five categories of the taxonomy and intuitively interpreting visual metaphors was developed so that appropriate cases can be recommended to sentiment visualization researchers. (4) The approach and usefulness of the exploration system were explained using user scenarios. (5) A case study was conducted to show that the provided system can be analyzed from various perspectives. (6) The usability of the exploration system was demonstrated through a verification targeting experts. The proposed system allows researchers and analysts to intuitively grasp “what types of visual metaphor method and idea should be equipped to visualize sentiment data in an easier way to understand.”","PeriodicalId":50360,"journal":{"name":"Information Visualization","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139774341","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

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

Visual analytics of soccer player performance using objective ratings 利用客观评分对足球运动员的表现进行可视化分析

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2024-01-12 DOI: 10.1177/14738716231220539

Marina Evers, Adrian Derstroff, Simon Leistikow, Tom Schneider, Larissa Mallepree, Jan Stampke, Moritz Leisgang, Sebastian Sprafke, Melina Schuhl, Niklas Krefft, Felix Droese, Lars Linsen

引用次数: 0