Advanced Machine Learning and Social Media For Natural Disasters Response
Date: 20 mars 2024 – 12h30-13h30
Advanced Machine Learning and Social Media For Natural Disasters Response
Social media and online platforms are crucial for understanding the impact of a natural disaster, especially right after it happens. People on social media share important details about things like damage to important buildings and roads, how bad the damage is, and how the victims are doing. This kind of information from social media can help speed up the response to a crisis.
The real-time information from social media can enhance situational awareness conducted by the emergency organization. Situational awareness means having a clear picture what is happening in the disaster area and understanding the significance of the event.
The presentation focuses on how advanced machine learning can improve classification and geolocation of social media content during natural disasters.
Short bio:
Hafiz Budi Firmansyah is a researcher and PhD candidate in Information Systems at University of Geneva, Switzerland. He has previously worked as an IT Consultant in the public and private sector. He obtained his Master degree in Informatics at Université de Paris, France in 2016. He is a lecturer and researcher at Department of Informatics Sumatra Institute of Technology, Indonesia.
His research focuses on machine learning and social media for disaster response. Specifically, the research attempts to automatically classify and predict the information from social media by using a machine learning approach during natural disasters.
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