Lecture17 - 50% more likely to be obese How networks shape...

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Sociology 10/22/2010 Lecture 17: Network Analysis and Dynamics of Diffusion Final Friday December 10, 2 pm, Barton 100 East Social network data: A simple example RB JT AF AP CM RB - 1 1 1 1 JT 1 - 1 1 1 AF 1 1 - 1 1 AP 1 1 1 - 1 CM 1 1 1 1 - Adjacency matrix (with k= 5 actors) -Relationships—whether the have been in contact over the last 2 weeks—have they initiated a contact with the other person over the last 2 weeks Density : The interconnectedness of the actors in a network o Measured as the number of observed ties divided by the number of all possible ties (k 2 -k) = 5 2 -5 = 20 o Example: mine= 20/20 = 100% Study -Largest component of the Framingham social network, 2000 Yellow=obese, Green=not obese -Sizes of nodes are directly proportional to BMI -Findings: The extent to which people are obese is largely a function of if the people they are connected to are obese -Friend who was obese
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Unformatted text preview: 50% more likely to be obese How networks shape individuals • By providing a frame of reference for what is “normal” o Local areas of networks act as “prisms” through which more general social norms are filtered • Through social influence o Suggestion, encouragement, pressure, and other forms of informal control o Mutual influence on experiences and activities • By providing role models • Through physical contact Diffusion • Diffusion : The processes by which something (e.g., an idea, innovation, disease) spreads through a social system • What determines when a social actor adopts, receives, or “catches” something? o Individual-level factors o Structural factors (e.g., network connections, position)-Diagram: Prescribing drugs from physicians...
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This note was uploaded on 02/13/2011 for the course SOC 101 taught by Professor Cornwell during the Fall '08 term at Cornell.

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Lecture17 - 50% more likely to be obese How networks shape...

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