This interdisciplinary research project will examine human dynamics across social media and social networks and will focus on the modeling of information diffusion over both time and space. It also will study the connection between online activities and real world human behaviors. Because the research team will employ a broad range of different research approaches to study the processes through which people's behavior is reflected in electronic media, the project will yield new communication theories, knowledge-discovery tools, and computational models. It will facilitate the convergence of information and insights across a diverse set of fields, including spatial science, social media, communication, computer science, and social behavioral analysis. The project also will facilitate the adoption of computational applications and modeling approaches in behavioral and social science research. The investigators will conduct tests of two different scenarios (public response to disaster warnings and alerts and referendums of controversial social topics at state and national levels) to refine a new theory about communication dealing with memes, or reproducible messages. One product of the project will be a prototype social media outreach platform designed and tested in coordination with the city of San Diego's Office of Emergency Services. The prototype will facilitate rapid dissemination of official alerts and warnings notifications during disaster events via multiple social media channels to targeted populations. The platform will be designed to identify and recruit 1,000 social media volunteers based on their social network influence factors, thereby enabling government agencies to communicate more effectively to the public and to be better prepared for both natural disasters and human-related crises. The project also will provide research and educational opportunities for students in multiple disciplines, including geography, linguistics, computer science, social science, and communication.
People move in time and space, and while they do so, they communicate. With modern communication technologies, they leave traces of and refer to their behavior while they engage in everyday behavior. These informational echoes have enormous potential to provide insights into people's behavior. The research team will analyze the diffusion patterns of human messages, activities, and communications using computational methods, such as social network analysis, geographic information systems, and machine-learning, as well as traditional social scientific research methods, such as qualitative analysis, inferential statistics, and behavior analysis. The investigators will build an interdisciplinary research framework for studying human dynamics and information diffusion from a spatiotemporal modeling perspective. They will validate and improve the Multilevel Model of Meme Diffusion (M3D) communication theory for online human communications across social media and social networks. They will analyze the dynamic changes of spatiotemporal patterns with two scenarios of human dynamics (disaster warnings/alerts and referendum/propositions of controversial social topics) using computational predictive methods and agent-based modeling (ABM) approaches. They also will develop effective and accessible data processing, visualization, and analytical tools for social scientists to study human dynamics and information diffusion by combining high-performance computing, Web-based geographic information system tools, agent-based modeling, and open-source software. This project is supported through the NSF Interdisciplinary Behavioral and Social Sciences Research (IBSS) competition.
