Community

Rory Sie Member since: Tuesday, February 11, 2014

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.

Cristina Chueca Del Cerro Member since: Friday, May 15, 2020

I’m a PhD researcher at the University of Glasgow working on modelling national identity polarisation on social media platforms using ABMs.

agent-based models, social networks, python, R, NetLogo

Tom Brughmans Member since: Wednesday, September 24, 2014 Full Member Reviewer

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.

Szymon Talaga Member since: Tuesday, July 16, 2019 Full Member

MSc Psychology

PhD student in The Robert Zajonc Institute for Social Studies at the University of Warsaw.

network science; social networks; sociology; complex systems; ecological psychology; cognitive science; perception and action

Ian Dennis Miller Member since: Tuesday, February 16, 2016 Full Member

MA Social Psychology, BS Cognitive Science

PhD student at University of Toronto: memes, social networks, contagion, agent based modeling, synthetic populations

Muaz Niazi Member since: Sunday, June 07, 2009 Full Member Reviewer

BE (Hons), MS CS, PhD

Muaz is a Senior Member of the IEEE and has more than 15 years of professional, teaching and research experience. Muaz has been working on Communication Systems and Networks since 1995. His BS project in 1995 was on the development of a Cordless Local Area Network. In 1996, his postgraduate project was on Wireless Connectivity of devices to Computers. In addition to his expertise as an Communications engineer, his areas of research interest are in the development of agent-based and complex network-based models of Complex Adaptive Systems. He has worked on diverse case studies ranging from Complex Communication Networks, Biological Networks, Social Networks, Ecological system modeling, Research and Scientometric modeling and simulation etc. He has also worked on designing and developing embedded systems, distributed computing, multiagent and service-oriented architectures.

Fabio Correa Duran Member since: Sunday, March 15, 2015

Physicist, Ms. C. Physics

I have been working in the software implementation of different kinds of complex networks inspired in real-life populations. My software may be classified on several categories: complex networks, Aedes aegypti development, dengue epidemics, cultural behavior of populations. I am also researching in education of Deaf people in Colombia.

Károly Takács Member since: Monday, October 20, 2014

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.

Xiaotian Wang Member since: Friday, March 28, 2014

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.

Cheddi Kiravu Member since: Tuesday, February 09, 2010

Electrical Power Engineering, Science (Physics, Mathematics, and Education)

Network ABMS in solar technology adoption in households

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