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SOC101Y1 (985)
Lecture 3

Lecture 3 Notes

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Matthias Koenig

SOC355Y1 Lecture #3 September 28, 2010 Monday office hours between 12 and 2 Last week you learned: - Network analysis argues that similar network structures have similar causes and similar effects - Random networks have very predictable structures: one component, low clustering, short path- length - Most networks are non-random. Networks are affected by: o Preferences for interaction o Contexts or foci in which contacts are made Transitivity Homophily- tendency for like to associate to like o Growth over time New nodes- change in structure, ties ties form through others, popular continue to be popular etc. - In particular- Simmels argument for separating form (sociologists to study) from content. Individuality is the result of network and resolving conflicts in network position. - Concrete network structures random networks Todays Outline - Theories of the Middle Range - What makes network theories different o Relations, not attributes o Networks not groups o Relations in the context of other relations - How to make your very own network theory o Formalist Theories
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