CiteVis : Visual Analysis of Overlapping Citation Intents as Dynamic Sets (Paper)
Faculty/Professorship: | Information Visualisation |
Author(s): | Agarwal, Shivam ![]() ![]() |
Publisher Information: | Bamberg : Otto-Friedrich-Universität |
Year of publication: | 2022 |
Pages: | 1-2 |
Language(s): | English |
Remark: | Created in the context of the 15th IEEE Pacific Visualization Symposium, 11.-14. April 2022 (Online). |
DOI: | 10.20378/irb-54949 |
Licence: | Creative Commons - CC BY - Attribution 4.0 International |
URL: | https://pvis2022.github.io/pvis2022/ https://s-agarwl.github.io/publication/Agarwal2... |
URN: | urn:nbn:de:bvb:473-irb-549496 |
Abstract: | A scientific article can be cited with different intents over several years. The citation intents can be inferred by classifying the citation text into different categories. With multiple citations to the same article, the citation intent categories overlap, making their analysis more challenging. We model the categories as dynamic sets and propose an approach to visualize temporal citation trends of an article across overlapping citation intents. The approach supports comparison between the citation trends of two seed articles of interest. The implemented prototype supports searching and selecting seed articles from a Semantic Scholar dataset. |
GND Keywords: | Zitat; Kontext; Menge; Visualisierung |
Keywords: | citation context, dynamic sets, visualization |
DDC Classification: | 004 Computer science |
RVK Classification: | ST 274 |
Peer Reviewed: | Ja |
International Distribution: | Nein |
Type: | Conferenceobject |
URI: | https://fis.uni-bamberg.de/handle/uniba/54949 |
Release Date: | 13. October 2022 |
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originated at the
University of Bamberg
University of Bamberg