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Social network analysis has an especially long tradition in the social science. In recent years, a dramatically increased visibility of SNA, however, is owed to statistical physicists. Among many, Barabasi-Albert model (BA model) has attracted particular attention because of its mathematical properties (i.e., obeying power-law distribution) and its appearance in a diverse range of social phenomena. BA model assumes that nodes with more links (i.e., “popular nodes”) are more likely to be connected when new nodes entered a system. However, significant deviations from BA model have been reported in many social networks. Although numerous variants of BA model are developed, they still share the key assumption that nodes with more links were more likely to be connected. I think this line of research is problematic since it assumes all nodes possess the same preference and overlooks the potential impacts of agent heterogeneity on network formation. When joining a real social network, people are not only driven by instrumental calculation of connecting with the popular, but also motivated by intrinsic affection of joining the like. The impact of this mixed preferential attachment is particularly consequential on formation of social networks. I propose an integrative agent-based model of heterogeneous attachment encompassing both instrumental calculation and intrinsic similarity. Particularly, it emphasizes the way in which agent heterogeneity affects social network formation. This integrative approach can strongly advance our understanding about the formation of various networks.
Andrew Bell (Ph.D. 2010, Michigan) was a Research Fellow in the Environment and Production Technology Division at the International Food Policy Research Institute (IFPRI) in Washington, DC. His current research portfolio focuses on the use of field instruments – such as discrete choice experiments, framed field experiments, randomized control trials – to inform behavior in agent-based models of coupled human-natural systems. Prior to this post, Andrew was a post-doctoral research fellow at The Earth Institute at Columbia University, where he focused on developing applications for paleo-climate histories.
Leonardo Grando is a Ph.D. Student at the University of Campinas (UNICAMP) in Brazil. I am interested in complex systems, agent-based simulation, artificial intelligence, the Internet of Things, programming, and machine learning tools. I have expertise in Netlogo, Python, R, Latex, SQL, and Linux tools.
My Ph.D. work project is an IoT devices (UAVs) swarm agent-based modeling simulation (ABMS) aiming the perpetual flight. The workflow is Netlogo to ABMS simulate, Python and R to data analysis, and I use Latex for my thesis writing.
I’m a Research Associate in Computational Social Science at Durham University working on a project that intends to produce more realistic artificial social networks (RASN) for simulation by creating a taxonomy of existing generator papers, accessible as an interactive, open-access database, in addition to exploring the interdependencies of social network’s structural properties. I obtained my PhD from University of Glasgow in (2023) where I was working on modelling national identity polarisation on social media platforms using ABMs.
agent-based models, social networks, echo chambers, polarisation
Julia, R, NetLogo, Python
Dr. Saeed Moradi received his Ph.D. in Civil Engineering from Texas Tech University in Lubbock, Texas. Saeed has 11+ years of experience in research, policymaking, housing sector, construction management, and structural engineering. His career developed his enthusiasm for the enhancement of post-disaster recovery plans. Through his research on disaster recovery, community resilience, and human-centered complex systems, Saeed aims to bridge the gap between social sciences and civil/infrastructure engineering.
Community and Infrastructure Resilience
Disaster Recovery
Complex Systems Modeling
Agent-Based Modeling
System Dynamics
Machine Learning
Pattern Recognition
Data Mining
Spatial Analysis and Modeling
Construction Management
Building Information Modeling
Anna Pagani is an architect and doctoral researcher under the supervision of Prof. Claudia R. Binder in the interdisciplinary laboratory for Human-Environment Relations in Urban Systems (HERUS) at École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. In her PhD, she works closely with tenants, housing providers and practitioners to provide housing that is not only environmentally but also socioculturally sustainable.
Her research interests revolve around the relationship between the human and material components of the built environment, and more specifically on the introduction of a systems perspective to housing studies.
Dr. William G. Kennedy, “Bill,” is continuing to learn in a third career, this time as an academic, a computational social scientist.
His first a career was in military service as a Naval Officer, starting with the Naval Academy, Naval PostGraduate School (as the first computer science student from the Naval Academy), and serving during the Cold War as part of the successful submarine-based nuclear deterrent. After six years of active duty service, he served over two decades in the Naval Reserves commanding three submarine and submarine-related reserve units and retiring after 30 years as a Navy Captain with several personal honors and awards.
His second career was in civilian public service: 10 years at the Nuclear Regulatory Commission and 15 years with the Department of Energy. At the NRC he rose to be an advisor to the Executive Director for Operations and the authority on issues concerning the reliance on human operators for reactor safety, participating in two fly-away accident response teams. He left the NRC for a promotion and to lead, as technical director, the entrepreneurial effort to explore the use of light-water and accelerator technologies for the production of nuclear weapons materials. That work led to him becoming the senior policy officer responsible for strategic planning and Departmental performance commitments, leading development of the first several DOE strategic plans and formal performance agreements between the Secretary of Energy and the President.
Upon completion of doctoral research in Artificial Intelligence outside of his DOE work, he began his third career as a scientist. That started with a fully funded, three-year post-doctoral research position in cognitive robotics at the Naval Research Laboratory sponsored by the National Academy of Science and expanding his AI background with research in experimental Cognitive Science. Upon completion, he joined the Center for Social Complexity, part of the Krasnow Institute for Advanced Study at George Mason University in 2008 where he is now the Senior Scientific Advisor. His research interests range from cognition at the individual level to models of millions of agents representing individual people. He is currently leading a multi-year project to characterize the reaction of the population of a mega-city to a nuclear WMD (weapon of mass destruction) event.
Dr. Kennedy holds a B.S. in mathematics from the U.S. Naval Academy, and Master of Science in Computer Science from the Naval PostGraduate School, and a Ph.D. in Information Technology from George Mason University and has a current security clearance. Dr. Kennedy is a member of Sigma Xi, the American Association for the Advancement of Science (AAAS), the Association for Computing Machinery (ACM), and a life member of Institute of Electrical and Electronics Engineers. He is a STEM volunteer with the Senior Scientists and Engineers/AAAS Volunteer Program for K-12 science, technology, engineering, and mathematics education in the DC-area schools.
Cognitive Science, Computational Social Science, Social Cognition, Autonomy, Cognitive Robotics
Aniruddha Belsare is a disease ecologist with a background in veterinary medicine, interspecific transmission, pathogen modeling and conservation research. Aniruddha received his Ph.D. in Wildlife Science (Focus: Disease Ecology) from the University of Missouri in 2013 and subsequently completed a postdoctoral fellowship there (University of Missouri, May 2014 – June 2017). He then was a postdoctoral fellow in the Center for Modeling Complex Interactions at the University of Idaho (June 2017 - March 2019) and later a Research Associate with the Boone and Crockett Quantitative Wildlife Center, Michigan State University (March 2019 - Jan 2021). He was a Research Scientist in the Civitello Disease Ecology Lab at Emory University from Jan 2021 to Jan 2023. Currently, Aniruddha is an Assistant Professor of Disease Ecology at the College of Forestry, Wildlife & Environment / College of Veterinary Medicine at Auburn University.
My research interests primarily lie at the interface of ecology and epidemiology, and include host-pathogen systems that are of public health or conservation concern. I use ecologic, epidemiologic and model-based investigations to understand how pathogens spread through, persist in, and impact host populations. Animal disease systems that I am currently working on include canine rabies, leptospirosis, chronic wasting disease, bighorn sheep pneumonia, raccoon roundworm (Baylisascaris procyonis), chytridiomycosis, and Lyme disease.
I am an anthropological archaeologist with broad interests in hunter-gatherers, lithic technology, human evolution, and complex systems theory. I am particularly interested in understanding processes of long term social, evolutionary, and adaptational change among hunter-gatherers, specifically by using approaches that combine archaeological data, ethnographic data, and computational modeling.
Applications of agent-based modeling and complexity theory to real-world problems. I am particular interested in stigmergic polyagents, their relation to the path integral formalization of quantum physics, and their application to combinatorially explosive problems, but also work extensively in modeling social systems.
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