A Hierarchical Decision-making Process in Social Networks for Disaster Management 机翻标题: 暂无翻译,请尝试点击翻译按钮。

会议集名/来源
IISE Annual Conference and Expo 2018: Orlando, Florida, USA, 19-22 May 2018, Volume 3 of 3
出版年
2018
页码
1832-1837
会议地点
Orlando
语种
eng
作者单位
Systems and Industrial Engineering, The University of Arizona;Systems and Industrial Engineering, The University of Arizona
作者
Seunghan Lee;Young-Jun Son
摘要
The social media have been increasingly used for disaster management (DM) via providing real time data on a broad scale. For example, some smartphone applications (e.g. Disaster Alert and Federal Emergency Management Agency (FEMA) App) can be used to increase the efficiency of prepositioning supplies and to enhance the effectiveness of disaster relief efforts. To maximize utilities of these apps, it is imperative to have robust human behavior models in social networks with detailed expressions of individual decision-making processes and of the interactions among people. In this paper, we introduce a hierarchical human behavior model by associating extended Decision Field Theory (e-DFT) with the opinion formation and innovation diffusion models. Particularly, its expressiveness and validity are addressed in three ways. First, we estimate individual's choice patterns in social networks by deriving people's asymptotic choice probabilities within e-DFT. Second, by analyzing opinion formation models and innovation diffusion models in different types of social networks, the effects of neighbor's opinions on people and their interactions are demonstrated. Finally, an agent-based simulation is used to trace agents' dynamic behaviors in different scenarios. The simulated results reveal that the proposed models can be used to establish better disaster management strategies in natural disasters.
机翻摘要
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关键词
Disaster Management;Social Media;Decision Field Theory;Opinion Formation;Innovation Diffusion;Agent-based Simulation
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