Social Medium Data
Social media data analysis leverages the vast amount of user-generated content to understand societal trends, behaviors, and opinions. Current research focuses on developing and applying advanced machine learning models, including transformer networks and graph neural networks, to analyze this complex, multimodal data for tasks such as sentiment analysis, event detection, and bias identification. This field is significant for its potential to improve public health interventions (e.g., identifying mental health risks), inform policy decisions (e.g., understanding public opinion on energy policy), and enhance our understanding of social dynamics across diverse cultures and contexts.
Papers
Community-based Behavioral Understanding of Crisis Activity Concerns using Social Media Data: A Study on the 2023 Canadian Wildfires in New York City
Khondhaker Al Momin, Md Sami Hasnine, Arif Mohaimin Sadri
Leveraging Social Media Data to Identify Factors Influencing Public Attitude Towards Accessibility, Socioeconomic Disparity and Public Transportation
Khondhaker Al Momin, Arif Mohaimin Sadri, Md Sami Hasnine
Natural Disaster Analysis using Satellite Imagery and Social-Media Data for Emergency Response Situations
Sukeerthi Mandyam, Shanmuga Priya MG, Shalini Suresh, Kavitha Srinivasan
Network Wide Evacuation Traffic Prediction in a Rapidly Intensifying Hurricane from Traffic Detectors and Facebook Movement Data: A Deep Learning Approach
Md Mobasshir Rashid, Rezaur Rahman, Samiul Hasan