Abstract People increasingly use Social Media (SM) platforms such as Twitter and Facebook
during disasters and emergencies to post situational updates including reports of injured or …

Fine-tuning pre-trained models for downstream tasks is mainstream in deep learning.
However, the pre-trained models are limited to be fine-tuned by data from a specific …

Mechanisms for sharing information in a disaster situation have drastically changed due to
new technological innovations throughout the world. The use of social media applications …

In times of crisis, the prompt and precise classification of disaster-related information shared
on social media platforms is of paramount importance for effective disaster response and …

In recent days, humanitarian organizations rely on social media like Twitter for situational
awareness during the disaster. Millions of tweets are posted on Twitter in the form of text or …

In the age of rapid internet expansion, social media platforms like Twitter have become
crucial for sharing information, expressing emotions, and revealing intentions during crisis …

During natural disasters, people often use social media platforms, such as Twitter, to post
information about casualties and damage produced by disasters. This information can help …

The role of social media in fashion industry has been blooming as the years have continued
on. In this work, we investigate sentiment analysis for fashion related posts in social media …

The steady growth of the Internet has increased the amount of user-generated data on the
web. Patients are now commonly posting their reviews after consuming the medicines to …

Multimodal land cover classification (MLCC) is a fundamental problem in remote sensing
interpretation, which can obtain excellent performance on account of the complementary …