In this paper, we explore the design space of word-sized visualizations—small graphics, usually the same size as a word, that visualize data in or related to a text—for displaying and exploring categories in social media feeds such as Twitter streams. Social media contributions are typically microposts, which allow us to attach word-sized visualizations to show category assignment, diversity, or development. We consider and combine word-sized visualizations made up of basic marks and visual variables, existing word-sized visualization concepts, as well as large text visualizations. In an application example we show how word-sized visualizations can evince context changes within a discussion on Twitter and reveal topic diversity.
%0 Generic
%1 ivapp21
%A Huth, Franziska
%A Blascheck, Tanja
%A Koch, Steffen
%A Utz, Sonja
%A Ertl, Thomas
%B Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
%D 2021
%I SciTePress
%K 2021 myown vis(us) vis-gis visus:blaschta visus:ertl visus:huthfa visus:kochsn
%P 256-265
%R 10.5220/0010328602560265
%T Word-sized Visualizations for Exploring Discussion Diversity in Social Media
%U https://www.scitepress.org/Papers/2021/103286/103286.pdf
%V 3 IVAPP
%X In this paper, we explore the design space of word-sized visualizations—small graphics, usually the same size as a word, that visualize data in or related to a text—for displaying and exploring categories in social media feeds such as Twitter streams. Social media contributions are typically microposts, which allow us to attach word-sized visualizations to show category assignment, diversity, or development. We consider and combine word-sized visualizations made up of basic marks and visual variables, existing word-sized visualization concepts, as well as large text visualizations. In an application example we show how word-sized visualizations can evince context changes within a discussion on Twitter and reveal topic diversity.
%@ 978-989-758-488-6
@conference{ivapp21,
abstract = {In this paper, we explore the design space of word-sized visualizations—small graphics, usually the same size as a word, that visualize data in or related to a text—for displaying and exploring categories in social media feeds such as Twitter streams. Social media contributions are typically microposts, which allow us to attach word-sized visualizations to show category assignment, diversity, or development. We consider and combine word-sized visualizations made up of basic marks and visual variables, existing word-sized visualization concepts, as well as large text visualizations. In an application example we show how word-sized visualizations can evince context changes within a discussion on Twitter and reveal topic diversity.},
added-at = {2021-03-02T09:38:14.000+0100},
author = {Huth, Franziska and Blascheck, Tanja and Koch, Steffen and Utz, Sonja and Ertl, Thomas},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/28545da5296637c29dd54c71085df17c1/franziskahuth},
booktitle = {Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications},
doi = {10.5220/0010328602560265},
eventdate = {2021},
interhash = {ac227dd5804709ab6f5f12f622a70658},
intrahash = {8545da5296637c29dd54c71085df17c1},
isbn = {978-989-758-488-6},
keywords = {2021 myown vis(us) vis-gis visus:blaschta visus:ertl visus:huthfa visus:kochsn},
language = {english},
organization = {INSTICC},
pages = {256-265},
publisher = {SciTePress},
timestamp = {2022-06-07T14:22:19.000+0200},
title = {Word-sized Visualizations for Exploring Discussion Diversity in Social Media},
url = {https://www.scitepress.org/Papers/2021/103286/103286.pdf},
volume = {3 IVAPP},
year = 2021
}