Enhancing Dengue Awareness: A Comprehensive System for Filtering Thai Social Media Posts

Dengue fever poses a significant global public health challenge, particularly in regions with tropical and sub-tropical climates. Over the past six decades, Thailand has witnessed a surge in dengue fever outbreaks, reporting over 50,000 cases annually. Addressing these outbreaks effectively requires contin-uous public awareness initiatives and active community engagement. Interestingly, today, public awareness of dengue fever is significantly driven by posts on social media platforms. However, the sheer volume and diversity of posts may lead to crucial dengue- related messages being overshadowed. This paper thus focuses on developing the data filter component, which employs a deep learning technique to automatically classify the each individual Thai post containing dengue-specific keywords into two categories: dengue-related and dengue-unrelated. Essentially, the data filter component serves as the core engine of the TanRabad-AWARE system, aiming to streamline and prioritize crucial information from social media platforms to enhance dengue public awareness and promote the prevention and control of dengue outbreaks.