ESS 109/209: Biological and Social Networks
This course introduces the analysis of social and biological networks with a focus on field data collected by interdisciplinary environmental and health scientists. Beginning from the premise that structure emerges from relationships between individual entities, we will concentrate in particular on the measurement of relationships, emphasizing especially practical methodology for mixed-method fieldwork suitable for interdisciplinary biosocial sciences (e.g., earth system science, epidemiology, demography, anthropology, conservation science). Topics include: social relationships in humans and other animals, ecological networks (e.g., trophic relationships, mutualistic interactions), epidemiological networks, research design for collecting relational data, naturalistic observation, ethnographic network methods, sampling, data quality, missing data, graphs and graph theory, structural measures (e.g., density, centrality and centralization, clustering and community detection, embeddedness), network evolution, network diffusion, emergence, egocentric networks, multi-mode/multi-layer networks, inference for sampled networks. All computation and visualization will be done in R so some familiarity is assumed.
This is a new class that I will offer in Winter 2020. I have previously taught a graduate class in social network analysis. I have also organized a Workshop in Social Network Analysis for Anthropologists at the 2018 and 2019 AAPAs. This workshop includes extensive notes on doing network analysis in R.