Community

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

Simone Righi Member since: Tuesday, March 17, 2015

Ph.D. In Economics

Networks Theory, Applied Microeconomics, Industrial Organization and Social Interactions.

kianercy Member since: Wednesday, January 04, 2012

Msc. Mechanical Eng., Msc. Chemical Eng.

Adapting Agents on Evolving Networks: An evolutionary game theory approach

Arezo Bodaghi Member since: Tuesday, January 30, 2018

Master of science

My profound interest in networks convinced me to work in these subjects and start my master project on an application of social network analysis for detecting organized fraud in Automobile insurance, which helps to flag groups of fraudsters. The key point of this project is simply to find fraudulent rings, while the most of traditional methods have only taken opportunistic fraud into consideration. My duty in research is to design an algorithm for identifying cyclic components, then to be compared with theoretical ones. This project showed me how networks are used in the analysis of relations.

Valentina Guleva Member since: Monday, November 14, 2016

Modeling and simulation of complex systems, particularly, interbank networks; economic models and critical phenomena modeling

Matteo Morini Member since: Friday, February 22, 2019 Full Member

PhD, Computer Science, ENS Lyon, MS, Economics, University of Turin

Furkan Gürsoy Member since: Thursday, August 02, 2018 Full Member

Ph.D., Management Information Systems, Boğaziçi University, M.Sc., Data Science, Istanbul Şehir University, B.Sc., Management Information Systems, Boğaziçi University

Furkan Gürsoy received the BS in Management Information Systems from Boğaziçi University, Turkey, and the MS in Data Science from İstanbul Şehir University, Turkey. He is currently a PhD Candidate at Boğaziçi University. He previously worked as an IS/IT Consultant and a Machine Learning Engineer with the industry for several years. He held a Visiting Researcher Position with IMT Atlantique, France, in 2020. His research interests include complex networks, machine learning, simulation, and broad data science.

network science, machine learning, simulation, data science.

André Calero Valdez Member since: Wednesday, January 17, 2018

Dr. phil.

André Calero Valdez does research on Computational Communication Science investigating the influence of network structure and algorithms on communication flow using agent-based modeling.

Zhanli Sun Member since: Thursday, January 27, 2011 Full Member Reviewer

PhD

Agent based modelling;
Land use/land cover change;
Payment for ecosystem services;
Bayesian Network;
System Dynamics

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