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Shipeng Sun Member since: Mon, Sep 09, 2013 at 08:52 PM Full Member

PhD

SHIPENG SUN is an Assistant Professor in the Department of Geography and Environmental Science at Hunter College and the Earth and Environmental Sciences Program at Graduate Center, The City University of New York, New York, NY 10065. E-mail: shipeng.sun@hunter.cuny.edu.

Sociospatial network analysis, geovisualization, GIS algorithms, agent-based complexity modeling, human–environment systems, and urban geography

Alessandro Sciullo Member since: Mon, Nov 11, 2013 at 06:20 PM

Political Science

Current main research interests are concerned on diffusion of ICT among social actors of territorial systems: citizens(individuals and households), enterprises and governmental bodies. Most used methodological tools are , so far, multivariate statistics and Social Network Analysis.
I’d like to apply an ABM approach in the context of my PhD research project, aimed to observe the different modes of collaboration among universities and enterprises and tehir different effectiveness in terms of creation and spread of new knowledge.

Rory Sie Member since: Tue, Feb 11, 2014 at 10:14 AM

dr., MSc.

Mainly interested in studying social networks of learners, teachers, and innovators. Uses Social Network Analysis, but also sentiment analysis, data mining, and recommender system techniques.

Xiaotian Wang Member since: Fri, Mar 28, 2014 at 02:23 AM

PHD of Engineering in Modeling and Simulation, Proficiency in Agent-based Modeling

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.

Rohitash Banyal Member since: Sun, Apr 13, 2014 at 11:27 AM

M.Tech, PhD

Cloud Computing Security, Network Security ,Software Engineering

Federico Bianchi Member since: Mon, Apr 14, 2014 at 09:21 AM Full Member

Ph.D., Economic Sociology and Labour Studies, University of Milan - University of Brescia (Italy), M.A., Sociology, University of Turin (Italy), B.A., Philosophy, University of Milan (Italy)

Social scientist based in Milan, Italy. Post-doctoral researcher in Sociology at the Department of Social and Political Sciences of the University of Milan (Italy), member of the Behave Lab. Adjunct professor of Social Network Analysis at the Graduate School in Social and Political Sciences of the University of Milan.

  • the link between economic exchange, solidarity, and inter-group conflict
  • peer-review evaluation in scientific publishing
  • integrating Agent-Based Modelling (ABM) with Social Network Analysis (SNA)

Aaron Bramson Member since: Tue, Jul 01, 2014 at 12:36 PM Full Member

Ph.D. Philosophy and Political Science, University of Michigan, M.S. Mathematics, Northeastern University, B.S. Economics, University of Florida, B.A. Philosophy, University of Florida

Dr. Aaron Bramson is principal investigator of the AI Strategy Center of GA technologies in Tokyo, Japan, as well as an Affiliate Researcher in the Department of General Economics of Ghent University in Belgium. His research specialty is complexity science, especially methodologies for modeling complex systems. Research topics span across disciplines: measures of polarization and diversity, belief measure interoperability, integrating geospatial and network analyses for measuring walkability and neighborhood identification, and myriad applications in artificial intelligence and data visualization. He received his Ph.D. from the University of Michigan in a joint program with the departments of Political Science and Philosophy as well as an M.S. in Mathematics from Northeastern University.

Complex systems, agent-based modeling, social simulation, computational models, network models, network theory, methodology, philosophy of science, ontology, epistemology, ethics, artificial intelligence, big data analysis, geospatial data analysis,

Davide Secchi Member since: Tue, Jul 08, 2014 at 10:58 PM Full Member

PhD in Business Administration

I am Professor of Management at Paris School of Business and have held positions at the University of Southern Denmark, Bournemouth University (UK), University of Wisconsin (US), and at the University of Insubria (Italy). My current research efforts are on socially-based decision making, agent-based modeling, cognitive processes in organizations and socially responsible behavior in organizations. With a coauthor network of 50 colleagues located in over 10 different countries, I have published 126 (as of 2025) among articles, book chapters, and books. The monograph Computational organizational cognition (2021, Emerald), and the edited Agent-Based Simulation of Organizational Behavior with M. Neumann (2016, Springer Nature) specifically target computational simulation research in the social sciences. The book How do I Develop an Agent-Based Model? (2022, Elgar) is the first specifically written for business and management scholars.

My simulation research focuses on the applications of ABM to organizational behavior studies. I study socially-distributed decision making—i.e., the process of exploiting external resources in a social environment—and I work to develop its theoretical underpinnings in order to to test it. A second stream of research is on how group dynamics affect individual perceptions of social responsibility and on the definition and measurement of individual social responsibility (I-SR).

Tom Brughmans Member since: Wed, Sep 24, 2014 at 07:08 PM Full Member

PhD in Archaeology, University of Southampton (completion 13-10-2014), MSc Archaeological Computing (Spatial Technologies), University of Southampton, MA Archaeology, University of Leuven, BA Archaeology of Syro-Palestine, University of Leuven

My research aims to explore the potential of network science for the archaeological discipline. In my review work I confront the use of network-based methods in the archaeological discipline with their use in other disciplines, especially sociology and physics. In my archaeological work I aim to develop and apply network science techniques that show particular potential for archaeology. This is done through a number of archaeological case-studies: archaeological citation networks, visibility networks in Iron Age and Roman southern Spain, and tableware distribution in the Roman Eastern Mediterranean.

Károly Takács Member since: Mon, Oct 20, 2014 at 09:46 AM

PhD

My main research interests are the theoretical and experimental analysis of the dynamics of social networks, in relation to problems of cooperation and conflict.

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