{"title":"Gragnostics: Fast, Interpretable Features for Comparing Graphs","authors":"R. Gove","doi":"10.1109/IV.2019.00042","DOIUrl":"https://doi.org/10.1109/IV.2019.00042","url":null,"abstract":"Many analytical tasks, such as social network analysis, depend on comparing graphs. Existing methods are slow, or can be difficult to understand. To address these challenges, this paper proposes gragnostics, a set of 10 fast, layperson-understandable graph-level features. Each can be computed in linear time. To evaluate the ability of these features to discriminate different topologies and types of graphs, this paper compares a machine learning classifier using gragnostics to alternative classifiers, and the evaluation finds that the gragnostics classifier achieves higher performance. To evaluate gragnostics' utility in interactive visualization tools, this paper presents Chiron, a graph visualization tool that enables users to explore the subgraphs of a larger graph. Example usage scenarios of Chiron demonstrate that using gragnostics in a rank-by-feature framework can be effective for finding interesting subgraphs.","PeriodicalId":429883,"journal":{"name":"2019 23rd International Conference Information Visualisation (IV)","volume":"143 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133393047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Technique for Selection and Drawing of Scatterplots for Multi-Dimensional Data Visualization","authors":"T. Itoh, Asuka Nakabayashi","doi":"10.1109/IV.2019.00020","DOIUrl":"https://doi.org/10.1109/IV.2019.00020","url":null,"abstract":"Scatterplot matrix and parallel coordinate plots are well-used multi-dimensional data visualization techniques. These techniques have a problem that they need a very large screen space when an input dataset has an enormous number of dimensions. To solve this problem, we propose a method for selecting important scatterplots from all scatterplots generated from input datasets and for drawing the scatterplots as ”outliers” and ”regions enclosing non-outlier plots.” The technique is useful for users to determine whether to delete outliers from the datasets and form mathematical models of non-outlier plots. This paper introduces an example of visualization using this technique with a retail transaction dataset and climate values.","PeriodicalId":429883,"journal":{"name":"2019 23rd International Conference Information Visualisation (IV)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121947009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jukka Holm, Kaisa Väänänen, Mohammad Mushfiqur Rahman Remans
{"title":"User Experience Study of 360° Music Videos on Computer Monitor and Virtual Reality Goggles","authors":"Jukka Holm, Kaisa Väänänen, Mohammad Mushfiqur Rahman Remans","doi":"10.1109/IV.2019.00023","DOIUrl":"https://doi.org/10.1109/IV.2019.00023","url":null,"abstract":"360° videos are increasingly used for media and entertainment, but the best practices for editing them are not yet well established. In this paper, we present a study in which we investigated the user experience of 360° music videos viewed on computer monitor and VR goggles. The research was conducted in the form of a laboratory experiment with 20 test participants. During the within-subject study, participants watched and evaluated four versions of the same 360° music video with a different cutting rate. Based on the results, an average cutting rate of 26 seconds delivered the highest-quality user experience both for computer monitor and VR goggles. The cutting rate matched with participants’ mental models, and there was enough time to explore the environment without getting bored. Faster cutting rates made the users nervous, and a video consisting of a single shot was considered to be too static and boring.","PeriodicalId":429883,"journal":{"name":"2019 23rd International Conference Information Visualisation (IV)","volume":"152 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131959488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Weidong Huang, M. Ivanova, M. De Marsico, Minoru Nakayama
{"title":"Organising & Liaison Committee of Symposium","authors":"Weidong Huang, M. Ivanova, M. De Marsico, Minoru Nakayama","doi":"10.1109/iv.2018.00008","DOIUrl":"https://doi.org/10.1109/iv.2018.00008","url":null,"abstract":"Digital Humanities Knowledge Visualization, DHKV Theodor G Wyeld, Flinders University, AUS Sarah Kenderdine, National Institute of Experimental Arts, College of Fine Arts, University of New South Wales, AUS Advisory, Programme and reviewing committee: Theodor G Wyeld, Flinders University, AUS Sarah Kenderdine (Museum Victoria, Aust) Ekaterina Prasolova-Forland (NTNU, Trondheim) Teng-Wen Chang (NYUST, Taiwan) Brett Leavy (CyberDreaming, Aust) Malcolm Pumpa (QUT, Aust) Marinos Ioannides (CUT, Cyprus) Giovanni Issini (DFI, Italy)","PeriodicalId":429883,"journal":{"name":"2019 23rd International Conference Information Visualisation (IV)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121421720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Roberto Yuri Da Silva Franco, Alexandre Abreu de Freitas, Rodrigo Santos do Amor Divino Lima, Marcelle Pereira Mota, Carlos Gustavo Resque Dos Santos, Bianchi Serique Meiguins
{"title":"UXmood - A Tool to Investigate the User Experience (UX) Based on Multimodal Sentiment Analysis and Information Visualization (InfoVis)","authors":"Roberto Yuri Da Silva Franco, Alexandre Abreu de Freitas, Rodrigo Santos do Amor Divino Lima, Marcelle Pereira Mota, Carlos Gustavo Resque Dos Santos, Bianchi Serique Meiguins","doi":"10.1109/IV.2019.00038","DOIUrl":"https://doi.org/10.1109/IV.2019.00038","url":null,"abstract":"Evaluating User Experience (UX) is not a trivial task, and UX specialists have used a variety of tools to ana- lyze data collected from user tests, which causes difficulty in synchronizing the data. This paper presents UXmood, a tool that condenses multiple distinct data types (audio, video, text, and eye-tracking) in a dashboard of coordinated visualizations to ease the analysis process and allow to manage several projects where each project has several logs of user interaction. The tool replays sessions of tests and uses a combination of different sentiment analysis techniques to present a suggestion of user sentiment at any given time during the tasks. The visualizations support brushing and details-on-demand interactions and are synchronized with a temporal slider, allowing analysts to see specific moments of the tests freely. Also, the uses of the sentiment analysis in the collected data may improved the qualitative analysis of UX.","PeriodicalId":429883,"journal":{"name":"2019 23rd International Conference Information Visualisation (IV)","volume":"224 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127188342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}