Social Network Analysis
Ministrante: Soong Moon Kang
Associate Professor, University College London
Objetivos do curso
No final deste curso, os alunos deverão ser capazes de: – compreender as principais ferramentas e conceitos para analisar redes sociais – compreender questões relacionadas à coleta e análise de dados de redes sociais – identificar e discutir questões teóricas e metodológicas associadas a pesquisas em redes sociais
Programa completo – ementa e referências
Lecture Session: Introduction, Types of Networks, Data Collection – 21 de outubro, 2019; 7pm–10pm
Session 2 – Lecture Session: Fundamental Concepts, Centrality/Centralization, Power Law – 22 de outubro; 7pm–10pm
Session 3 – Lecture Session: Structural Equivalence and Blockmodeling, Brokerage and Structural Holes – 23 de outubro, 2019; 7pm–10pm
Session 4 – Lecture Session: Core-Periphery, Cohesive Subgroups, Community Detection, Small Worlds – 24 de outubro, 2019; 7pm–10pm
Session 5 – Lecture Session: Dyadic and Triadic Relationships, Structural Balance and Transitivity, Network Dynamics and Evolution, Information Cascades – 25 de outubro, 2019; 7pm–10pm
Session 6 – Lecture Session: Egocentric Networks, Cognitive Issues. Additional Topics on Data Collection Discussion Session: Project Selection – 26 de outubro, 2019; a definir
Referência
Wasserman, Stanley, and Katherine Faust. Social Network Analysis: Methods and Applications, Cambridge University Press, 1994. Artigos relevantes para o curso
Taxa de inscrição
Categoria Inscrição
Alunos ICMC-USP R$ 300,00
Alunos fora do ICMC-USP R$ 500,00
Pós Doutorandos R$ 1.000,00
Profissionais R$ 1.500,00
Realizar depósito bancário em:
Banco do Brasil
ICMC- Receita
Ag: 6845-4
C/C: 130.113-6
Política de Isenção
O interessado deverá enviar o pedido de 10 – 17/9 e justificativa de isenção para o e-mail ccex@icmc.usp.br Os pedidos serão apreciados pelo coordenador do curso, por ordem de recebimento e até o limite de isenções possíveis.
Inscrições até 15/10 em:
http://www.icmc.usp.br/e/a8d09
About the Instructor
Soong Moon Kang is an Associate Professor at University College London School of Management. His research interests include social network analysis, complex systems, computational social science, social psychology, innovation and creativity, organization theory, business strategy and entrepreneurship. His research has appeared in leading international academic publications including the Proceedings of the National Academy of Sciences (PNAS), Organization Science and Social Networks as well as in main popular press such as The Economist, BBC, Der Spiegel and American Scientist. He holds a Ph.D. in Management Science and Engineering, a M.A. in Sociology and a M.S. in Engineering-Economic Systems from Stanford University, and a degree of Diplom-Ingenieur in Mechanical Engineering from Technische Universität Berlin.