Disasters and responses have evolved over-time, and the evolution has been affected by various factors, such as societal change, climate change, and technological advance. To better prepare the future disasters, we need to estimate the evolution trend of the past disasters and the responses. This paper analyzes the academic articles of the field with networktext analyses. The analyses captured the word level and the topic level evolution over-time with statistical significance tests. Further, we turn the text mining results into the network analysis data to identify the key words and topics in the evolution paths. The proposed method suggests the swift of interests, i.e. the new ways of organizational interoperation, the evolution of logistic issues, in the disaster and response field.
|Number of pages||8|
|Journal||Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics|
|Publication status||Published - 2014|
|Event||2014 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2014 - San Diego, United States|
Duration: 2014 Oct 5 → 2014 Oct 8
Bibliographical notePublisher Copyright:
© 2014 IEEE.
All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering
- Control and Systems Engineering
- Human-Computer Interaction