Using social media data to construct and analyze knowledge graph for "7.20" Henan rainstorm flood event DOI Creative Commons

Haipeng Lu,

Shuliang Zhang,

Yu Gao

et al.

International Journal of Disaster Risk Reduction, Journal Year: 2024, Volume and Issue: unknown, P. 105129 - 105129

Published: Dec. 1, 2024

Language: Английский

Resilience assessment of linear transportation sections considering multi-dimensional time-varying couplings DOI
Zhi‐Quan Liu,

S. Chen,

Mo-mo Zhi

et al.

Engineering Structures, Journal Year: 2025, Volume and Issue: 335, P. 120343 - 120343

Published: April 18, 2025

Language: Английский

Citations

0
The media-psychological model of environmental risk perception DOI Creative Commons
Maxim Kaznacheev

Scientific Studios on Social and Political Psychology, Journal Year: 2024, Volume and Issue: 30(1), P. 27 - 38

Published: May 7, 2024

The article presents the results of a theoretical analysis on topic media-psychological aspects perception environmental risks and presentation author's media psychological model impact messages risks. presented examines processes stages involved in initial encounter with risk further outcomes their processing which can manifest information-seeking behaviour. According to model, changes are considered series initiated by attention information continue when behaviour is triggered. main models relied author this study Limited Capacity Model Motivated Mediated Message Processing describe message Risk Information Search Several additional communication dedicated consideration were also used mass influence Thus, dual persuasive considered, including Heuristic-Systematic Elaboration Likelihood Model, as well theories examining behaviour: Theory Management Planned Seeking

Language: Английский

Citations

1
Integrating social media and deep learning for real-time urban waterlogging monitoring DOI Creative Commons
Muhammad Waseem Boota, Shan‐e‐hyder Soomro, Muhammad Ozair Ahmad

et al.

Journal of Hydrology Regional Studies, Journal Year: 2024, Volume and Issue: 56, P. 102070 - 102070

Published: Nov. 19, 2024

Language: Английский

Citations

1
Multimodal Social Sensing for the Spatio-Temporal Evolution and Assessment of Nature Disasters DOI Creative Commons
Yu Chen, Zhiguo Wang

Sensors, Journal Year: 2024, Volume and Issue: 24(18), P. 5889 - 5889

Published: Sept. 11, 2024

Social sensing, using humans as sensors to collect disaster data, has emerged a timely, cost-effective, and reliable data source. However, research focused on the textual data. With advances in information technology, multimodal such images videos are now shared media platforms, aiding in-depth analysis of social sensing systems. This study proposed an analytical framework extract disaster-related spatiotemporal from Using pre-trained neural network location entity recognition model, integrates semantics with information, enhancing situational awareness. A case April 2024 heavy rain event Guangdong, China, Weibo demonstrates that content correlates more strongly rainfall patterns than alone, offering dynamic perception disasters. These findings confirm utility offer foundation for future research. The offers valuable applications emergency response, relief, risk assessment, witness discovery, presents viable approach safety monitoring early warning

Language: Английский

Citations

1
Using social media data to construct and analyze knowledge graph for "7.20" Henan rainstorm flood event DOI Creative Commons

Haipeng Lu,

Shuliang Zhang,

Yu Gao

et al.

International Journal of Disaster Risk Reduction, Journal Year: 2024, Volume and Issue: unknown, P. 105129 - 105129

Published: Dec. 1, 2024

Language: Английский

Citations

1