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SocioPedia+: a visual analytics system for social knowledge graph-based event explorationopen access

Authors
Nguyen, Tra MyChun, Hong -WooHwang, MyunggwonKwon, Lee -NamLee, Jae-MinPark, KangheeJung, Jason J.
Issue Date
Mar-2023
Publisher
PEERJ INC
Keywords
SocioPedia; Knowledge graph; Event detection and exploration; Visual analytics
Citation
PEERJ COMPUTER SCIENCE, v.9
Journal Title
PEERJ COMPUTER SCIENCE
Volume
9
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/67651
DOI
10.7717/peerj-cs.1277
ISSN
2376-5992
2376-5992
Abstract
In the recent era of information explosion, exploring event from social networks has recently been a crucial task for many applications. To derive valuable comprehensive and thorough insights on social events, visual analytics (VA) system have been broadly used as a promising solution. However, due to the enormous social data volume with highly diversity and complexity, the number of event exploration tasks which can be enabled in a conventional real-time visual analytics systems has been limited. In this article, we introduce SocioPedia+, a real-time visual analytics system for social event exploration in time and space domains. By introducing the dimension of social knowledge graph analysis into the system multivariate analysis, the process of event explorations in SocioPedia+ can be significantly enhanced and thus enabling system capability on performing full required tasks of visual analytics and social event explorations. Furthermore, SocioPedia+ has been optimized for visualizing event analysis on different levels from macroscopic (events level) to microscopic (knowledge level). The system is then implemented and investigated with a detailed case study for evaluating its usefulness and visualization effectiveness for the application of event explorations.
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소프트웨어대학 (소프트웨어학부)
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