相关论文: Signals from the Floods: AI-Driven Disaster Analys…

This paper presents our research on leveraging social media Big Data and AI to support hurricane disaster emergency response. The current practice of hurricane emergency response for rescue highly relies on emergency call centres. The more…

Rapid impact assessment in the immediate aftermath of a natural disaster is essential to provide adequate information to international organisations, local authorities, and first responders. Social media can support emergency response with…

The shared real-time information about natural disasters on social media platforms like Twitter and Facebook plays a critical role in informing volunteers, emergency managers, and response organizations. However, supervised learning models…

T\"urkiye is located on a fault line; earthquakes often occur on a large and small scale. There is a need for effective solutions for gathering current information during disasters. We can use social media to get insight into public…

During disasters, extracting causal relations from social media can strengthen situational awareness by identifying factors linked to casualties, physical damage, infrastructure disruption, and cascading impacts. However, disaster-related…

Social media generates an enormous amount of data on a daily basis but it is very challenging to effectively utilize the data without annotating or labeling it according to the target application. We investigate the problem of localized…

Microblogging platforms such as Twitter provide active communication channels during mass convergence and emergency events such as earthquakes, typhoons. During the sudden onset of a crisis situation, affected people post useful information…

Floods are the most common and among the most severe natural disasters in many countries around the world. As global warming continues to exacerbate sea level rise and extreme weather, governmental authorities and environmental agencies are…

Responding to natural disasters, such as earthquakes, floods, and wildfires, is a laborious task performed by on-the-ground emergency responders and analysts. Social media has emerged as a low-latency data source to quickly understand…

Tweet hashtags have the potential to improve the search for information during disaster events. However, there is a large number of disaster-related tweets that do not have any user-provided hashtags. Moreover, only a small number of tweets…

Natural disasters often result in a surge of social media activity, including requests for assistance, offers of help, sentiments, and general updates. To enable humanitarian organizations to respond more efficiently, we propose a…

This paper introduces a novel approach for multimodal sentiment analysis on social media, particularly in the context of natural disasters, where understanding public sentiment is crucial for effective crisis management. Unlike conventional…

Understanding how attitudes towards the Climate Emergency vary can hold the key to driving policy changes for effective action to mitigate climate related risk. The Oil and Gas industry account for a significant proportion of global…

In this paper, we present our methods for the MediaEval 2020 Flood Related Multimedia task, which aims to analyze and combine textual and visual content from social media for the detection of real-world flooding events. The task mainly…

In large-scale emergencies social media has become a key source of information for public awareness, government authorities and relief agencies. However, the sheer volume of data and the low signal-to- noise ratio limit the effectiveness…

In recent years, artificial intelligence (AI) has deeply impacted various fields, including Earth system sciences. Here, AI improved weather forecasting, model emulation, parameter estimation, and the prediction of extreme events. However,…

Social media is a primary medium for information diffusion during natural disasters. The social media ecosystem has been used to identify destruction, analyze opinions and organize aid. While the overall picture and aggregate trends may be…

Microblogging sites like Twitter and Weibo have emerged as important sourcesof real-time information on ongoing events, including socio-political events, emergency events, and so on. For instance, during emergency events (such as…

This paper examines collaborative sensemaking during severe weather events through the emerging phenomenon of "weatherfluencers" or content creators who livestream meteorological interpretation on platforms like YouTube. Drawing from…

Timely classification of humanitarian information from social media is critical for effective disaster response. However, deploying large language models (LLMs) for this task faces challenges in resource-constrained emergency settings. This…