M. John, E. Marbach, S. Lohmann, Florian Heimerl, T. Ertl
{"title":"MultiCloud: Interactive Word Cloud Visualization for the Analysis of Multiple Texts","authors":"M. John, E. Marbach, S. Lohmann, Florian Heimerl, T. Ertl","doi":"10.20380/GI2018.06","DOIUrl":null,"url":null,"abstract":"Word Clouds have gained an impressive momentum for summarizing text documents in the last years. They visually communicate in a clear and descriptive way the most frequent words of a text. However, there are only very few word cloud visualizations that support a contrastive analysis of multiple documents. The available approaches provide comparable overviews of the documents, but have shortcomings regarding the layout, readability, and use of white space. To tackle these challenges, we propose MultiCloud, an approach to visualize multiple documents within a single word cloud in a comprehensible and visually appealing way. MultiCloud comprises several parameters and visual representations that enable users to alter the word cloud visualization in different aspects. Users can set parameters to optimize the usage of available space to get a visual representation that provides an easy visual association of words with the different documents. We evaluated MultiCloud with visualization researchers and a group of domain experts comprising five humanities scholars.","PeriodicalId":230994,"journal":{"name":"Proceedings of the 44th Graphics Interface Conference","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 44th Graphics Interface Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20380/GI2018.06","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
Word Clouds have gained an impressive momentum for summarizing text documents in the last years. They visually communicate in a clear and descriptive way the most frequent words of a text. However, there are only very few word cloud visualizations that support a contrastive analysis of multiple documents. The available approaches provide comparable overviews of the documents, but have shortcomings regarding the layout, readability, and use of white space. To tackle these challenges, we propose MultiCloud, an approach to visualize multiple documents within a single word cloud in a comprehensible and visually appealing way. MultiCloud comprises several parameters and visual representations that enable users to alter the word cloud visualization in different aspects. Users can set parameters to optimize the usage of available space to get a visual representation that provides an easy visual association of words with the different documents. We evaluated MultiCloud with visualization researchers and a group of domain experts comprising five humanities scholars.