Bill Rand

Bio

Bill uses geospatial analytics to understand how geography influences the spread of information, often within the context of climate change and sustainability. He develops machine learning and agent-based models to understand how people spread information both online and offline, and how they take action on that information once they have it. His interests also include the development of tools, pedagogies, and methodologies to help stakeholders make more informed, data-driven decisions.

Publications

• A GENERALIZATION OF THRESHOLD-BASED AND PROBABILITY-BASED MODELS OF INFORMATION DIFFUSION , ADVANCES IN COMPLEX SYSTEMS (2023)
• Special Section on "Inverse Generative Social Science": Guest Editors? Statement , JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION (2023)
• Two decades of agent-based modeling in marketing: a bibliometric analysis , PROGRESS IN ARTIFICIAL INTELLIGENCE (2023)
• Classification of social media users with generalized functional data analysis , COMPUTATIONAL STATISTICS & DATA ANALYSIS (2022)
• Entropy-Based Characterization of Influence Pathways in Traditional and Social Media , 2022 IEEE 8TH INTERNATIONAL CONFERENCE ON COLLABORATION AND INTERNET COMPUTING, CIC (2022)
• Evolution of Intent and Social Influence Networks and Their Significance in Detecting COVID-19 Disinformation Actors on Social Media , SOCIAL, CULTURAL, AND BEHAVIORAL MODELING (SBP-BRIMS 2022) (2022)
• Agent-based modeling of new product market diffusion: an overview of strengths and criticisms , ANNALS OF OPERATIONS RESEARCH (2021)
• Apart we ride together: The motivations behind users of mixed-reality sports , JOURNAL OF BUSINESS RESEARCH (2021)
• Deep Agent: Studying the Dynamics of Information Spread and Evolution in Social Networks , ArXiv (2021)
• Inferring mechanisms of response prioritization on social media under information overload , SCIENTIFIC REPORTS (2021)