LitVis: a visual analytics approach for managing and exploring literature
Reading literature is essential to research. However, the explosive growth, the multidimensional attributes, and the complex relationships pose a tremendous challenge for researchers to understand and analyze literature efficiently. We propose LitVis, a visual analysis approach to help users manage...
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| Published in | Journal of visualization Vol. 26; no. 6; pp. 1445 - 1458 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.12.2023
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1343-8875 1875-8975 |
| DOI | 10.1007/s12650-023-00941-3 |
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| Abstract | Reading literature is essential to research. However, the explosive growth, the multidimensional attributes, and the complex relationships pose a tremendous challenge for researchers to understand and analyze literature efficiently. We propose LitVis, a visual analysis approach to help users manage and explore literature based on its metadata. LitVis allows users to select literature collection of interest and analyze them from their attributes, text, and citation networks. From the perspective of attribute values, LitVis supports users in understanding the distribution of literature and filtering individuals of interest. From the perspective of the text, LitVis uses the Latent Dirichlet Allocation model to extract topics from the literature and allows users to adjust the topic extraction results interactively. From the citation network perspective, LitVis enables users to analyze citation relationships within and between topics to help them understand research development. One use case and carefully designed interviews with domain experts validate the effectiveness of LitVis in the management and analysis of the literature. The results show that LitVis help users comprehensively identify the literature collection of interest and efficiently analyze the evolution of research topics.
Graphical abstract |
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| AbstractList | Reading literature is essential to research. However, the explosive growth, the multidimensional attributes, and the complex relationships pose a tremendous challenge for researchers to understand and analyze literature efficiently. We propose LitVis, a visual analysis approach to help users manage and explore literature based on its metadata. LitVis allows users to select literature collection of interest and analyze them from their attributes, text, and citation networks. From the perspective of attribute values, LitVis supports users in understanding the distribution of literature and filtering individuals of interest. From the perspective of the text, LitVis uses the Latent Dirichlet Allocation model to extract topics from the literature and allows users to adjust the topic extraction results interactively. From the citation network perspective, LitVis enables users to analyze citation relationships within and between topics to help them understand research development. One use case and carefully designed interviews with domain experts validate the effectiveness of LitVis in the management and analysis of the literature. The results show that LitVis help users comprehensively identify the literature collection of interest and efficiently analyze the evolution of research topics. Reading literature is essential to research. However, the explosive growth, the multidimensional attributes, and the complex relationships pose a tremendous challenge for researchers to understand and analyze literature efficiently. We propose LitVis, a visual analysis approach to help users manage and explore literature based on its metadata. LitVis allows users to select literature collection of interest and analyze them from their attributes, text, and citation networks. From the perspective of attribute values, LitVis supports users in understanding the distribution of literature and filtering individuals of interest. From the perspective of the text, LitVis uses the Latent Dirichlet Allocation model to extract topics from the literature and allows users to adjust the topic extraction results interactively. From the citation network perspective, LitVis enables users to analyze citation relationships within and between topics to help them understand research development. One use case and carefully designed interviews with domain experts validate the effectiveness of LitVis in the management and analysis of the literature. The results show that LitVis help users comprehensively identify the literature collection of interest and efficiently analyze the evolution of research topics. Graphical abstract |
| Author | Tian, Min Yuan, Xiaoru Li, Guozheng |
| Author_xml | – sequence: 1 givenname: Min orcidid: 0000-0002-7455-0748 surname: Tian fullname: Tian, Min organization: Key Laboratory of Machine Perception (Ministry of Education), School of AI, Peking University – sequence: 2 givenname: Guozheng surname: Li fullname: Li, Guozheng organization: School of Computer Science, Beijing Institute of Technology – sequence: 3 givenname: Xiaoru surname: Yuan fullname: Yuan, Xiaoru email: xiaoru.yuan@pku.edu.cn organization: Key Laboratory of Machine Perception (Ministry of Education), School of AI, Peking University, National Engineering Laboratory for Big Data Analysis and Application, Peking University |
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| Copyright | The Visualization Society of Japan 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Snippet | Reading literature is essential to research. However, the explosive growth, the multidimensional attributes, and the complex relationships pose a tremendous... |
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| SubjectTerms | Citation analysis Classical and Continuum Physics Computer Imaging Dirichlet problem Engineering Engineering Fluid Dynamics Engineering Thermodynamics Heat and Mass Transfer Pattern Recognition and Graphics Regular Paper Vision |
| Title | LitVis: a visual analytics approach for managing and exploring literature |
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