Dr. Nguyen receives NSF grant to turn social media activity into a disaster planning tool

data science academics and research

When disasters occur, people often turn to social media to share their concerns and frustrations. Dr. Long Nguyen, assistant professor of computer science and data science, seeks to tie that activity to aid emergency planning. The National Science Foundation CISE-MSI Research Expansion program has awarded him a $320,368 grant to pursue that goal.

Long Nguyen

“Our goal is to extract posts and their surrounding context from social media during a disaster event and filter out any disinformation and irrelevant posts,” says Dr. Nguyen. “We will then then analyze causal relationship between events.”

“The end result will be a tool that community authorities can use for disaster mitigation planning,” says Dr. Nguyen.

Dr. Nguyen will take a novel approach to event analysis under the umbrella of graph neural network and transfer learning, leveraging recent advances and opportunities in deep learning. Transfer learning is a machine learning method where a model used for one task is reused for another model.

“Transfer learning has never been explored to solve this kind of problem, but there are similarities in disasters, so it makes sense to use transfer learning to apply what we learn from one disaster event to another,” says Dr. Nguyen.

“Additionally, he says, “we can represent these events across domains in a graph form and their interaction creates a multi-perspective view. The graph neural network will adapt with the representation of these events and capture their relationship.”

Nguyen will model the resulting data-driven algorithms to emphasize the socio-economic aspects of the consequences and the cascading losses by allowing the system to adapt according to the community-based variables and the dynamics of the disasters.

Dr. Nguyen’s project will also generate new research opportunities for students from underrepresented communities.

“This project will expose Meharry SACS’s students to practical problems, lead to the exchange of knowledge and resources between institutions, and include expertise from a diverse team,” says Dr. Nguyen. “This is important to the project because it not only supports successful implementation, but also uses all possible resources to maximize our research findings.”

The title of Dr. Nguyen’s project is Collaborative Research: CISE-MSI: DP: IIS: Event Detection and Knowledge Extraction via Learning and Causality Analysis for Resilience Emergency Response. He will collaborate with faculty from the Wireless to Cloud Computing Laboratory at the Missouri University of Science and Technology.

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