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.

Lilian Alessa Member since: Friday, May 11, 2007 Full Member Reviewer

Ph.D., Cell Biology, University of British Columbia

Dr. Lilian Alessa, University of Idaho President’s Professor of Resilient Landscapes in the Landscape Architecture program, is also Co-Director of the University of Idaho Center for Resilient Communities. She conducts extensive research on human adaptation to environmental change through resilient design at landscape scales. Much of her work is funded by the National Science Foundation, including projects awarded the Arctic Observing Network, Intersections of Food, Energy and Water Systems (INFEWS) and the Dynamics of Coupled Natural Human Systems programs. Canadian-born and raised, Alessa received her degrees from the University of British Columbia. She also uses her expertise in social-ecological and technological systems science to develop ways to improve domestic resource security for community well-being, particularly through the incorporation of place-based knowledge. Her work through the Department of Homeland Security’s Center of Excellence, the Arctic Domain Awareness Center, involves developing social-technological methods to monitor and respond to critical environmental changes. Lil is a member of the National Science Foundation’s Advisory Committee for Environmental Research and Education and is on the Science, Technology and Education Advisory Committee for the National Ecological Observing Network (NEON). Professor Alessa also teaches a university landscape architecture capstone course: Resilient Landscapes with Professor Andrew Kliskey. Professor Alessa’s collaborative grant activity with Professor Andrew Kliskey, since coming to the university in 2013, exceeds 7 million USD to date. She has authored over a 100 publications and reports and has led the development of 2 federal climate resilience toolbox assessments, the Arctic Water Resources Vulnerability Index (AWRVI) and the Arctic Adaptation Exchange Portal (AAEP).

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