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Publication

Detecting damaged buildings using real-time crowdsourced images and transfer learning

This paper presents an automated way to extract the damaged buildings images after earthquakes from social media platforms such as Twitter and thus identify the particular user posts containing such images. After significant earthquakes, we can see images posted on social media platforms by individuals and media agencies owing to the mass usage of…
Publication

Disaster impacts surveillance from social media with topic modeling and feature extraction: case of Hurricane Harvey

This study analyzes the content of Twitter data collected during Hurricane Harvey to identify the data of the highest relevance for assessing the impacts on infrastructure through automatically grouping the tweets by topics of discussion. More specifically, the researchers aimed to answer three research questions: (1) What are the common themes of discu…

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