Blowing Seeds across Gardens : Visualizing Implicit Propagation of Cross-Platform Social Media Posts
Propagation analysis refers to studying how information spreads on social media, a pivotal endeavor for understanding social sentiment and public opinions. Numerous studies contribute to visualizing information spread, but few have considered the implicit and complex diffusion patterns among multipl...
Veröffentlicht in: | IEEE transactions on visualization and computer graphics. - 1996. - PP(2024) vom: 10. Sept. |
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1. Verfasser: | |
Weitere Verfasser: | , , , , , , |
Format: | Online-Aufsatz |
Sprache: | English |
Veröffentlicht: |
2024
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Zugriff auf das übergeordnete Werk: | IEEE transactions on visualization and computer graphics |
Schlagworte: | Journal Article |
Zusammenfassung: | Propagation analysis refers to studying how information spreads on social media, a pivotal endeavor for understanding social sentiment and public opinions. Numerous studies contribute to visualizing information spread, but few have considered the implicit and complex diffusion patterns among multiple platforms. To bridge the gap, we summarize cross-platform diffusion patterns with experts and identify significant factors that dissect the mechanisms of cross-platform information spread. Based on that, we propose an information diffusion model that estimates the likelihood of a topic/post spreading among different social media platforms. Moreover, we propose a novel visual metaphor that encapsulates cross-platform propagation in a manner analogous to the spread of seeds across gardens. Specifically, we visualize platforms, posts, implicit cross-platform routes, and salient instances as elements of a virtual ecosystem - gardens, flowers, winds, and seeds, respectively. We further develop a visual analytic system, namely BloomWind, that enables users to quickly identify the cross-platform diffusion patterns and investigate the relevant social media posts. Ultimately, we demonstrate the usage of BloomWind through two case studies and validate its effectiveness using expert interviews |
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Beschreibung: | Date Revised 13.09.2024 published: Print-Electronic Citation Status Publisher |
ISSN: | 1941-0506 |
DOI: | 10.1109/TVCG.2024.3456181 |