# Social Media Analytics for Disaster Response: Classification and Geospatial Visualization Framework
## 3 Methods
### Visualization  
#### 3.3.1 Web Server and User Interface (UI)  
We deployed our testing website on a cloud server rented from VULTR, configured identically to our local workstation used for model training. This uniform configuration ensures seamless integration between development and deployment environments, thereby optimizing performance and maintaining consistency across platforms. The website is hosted using Nginx, an open-source web server that acts as a reverse proxy and load-balancer. Nginx is widely recognized for its efficiency, scalability, and ability to manage a high volume of concurrent connections, making it particularly suitable for disaster response applications. Its lightweight, event-driven architecture facilitates rapid data-processing and response times, ensuring reliability and speed in cloud-based environments where system stability is critical.  
Although Nginx served as our primary web server due to its robust performance and scalability, alternative solutions exist. Apache, another widely adopted web server, offers extensive module support and advanced features for handling dynamic content and complex configurations. Additionally, the Python testing server provides a lightweight, development-oriented alternative that is commonly utilized for testing and debugging in the early stages of application development. The chosen server architecture effectively manages incoming data streams, supports visualization, and maintains high reliability under peak loads, key attributes for disaster response systems that depend on timely and accurate information dissemination.  
To enable the interactive visualization of categorized data, we developed the index.html page of our website using Leaflet, an open-source JavaScript library designed for web-based mapping applications. Leaflet facilitates the dynamic presentation of disaster-related data through an intuitive and interactive mapping interface. The system employs a set of 10 distinct, color-coded markers to represent different event categories, prioritizing incidents based on urgency. Markers in red, orange, and pink are designated for the most critical situations, particularly those posing immediate threats to human life. This visual prioritization mechanism enhances situational awareness by enabling emergency response teams to quickly identify and respond to the most urgent cases.  
The interactive map is designed to update continuously, providing a comprehensive overview of disaster-related reports classified by severity and type. Users can engage with the map by clicking on individual markers, which triggers a pop-up window displaying detailed information about specific incidents. This functionality supports rapid situational assessments and facilitates informed decision-making among emergency response personnel. To maintain a clear and interpretable interface, the HTML map dynamically cycles through 10 newly reported incidents every 20 s, preventing marker overcrowding while ensuring timely updates. This dynamic refresh mechanism allows response teams to focus on the most recent and relevant disaster events. The interactive capabilities of the system, such as clickable markers with pop-up information, enable efficient assessment of key details, including post content, geographic location, and event classification. Figure 3 illustrates the color-coded markers and their corresponding categorizations.