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Cmn 150v Midterm
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Gravity
Terms in this set (42)
multiplex network
individual tied to others in variety of ways (working together, living together...); produces intense local relationships
component
when the nodes are connected in one group
cycle
walk that ends where it began
Homophily
birds of a feather flock together
contact theory
opportunity; self-reinforcing path dependency
transaction theory
cost; common culture facilitates communication
Dialetic Theory
social pressure; current narrative/prejudices
evolution theory
social competition; group/kin selection
use new kind of node
often exclusive
use new attribute
very overlapping
Dichotomization
usually explicit or implicit, ties are in grey zone between 0 and 1 (strength of ties)
vertices
edges, arcs
nodes
links
sites
bonds
actors
ties, relations
network
graph
degree
number of links of each node
how many degrees in a link?
each adds 2 degrees, one for each node
in-degree
number of incoming links for each node
out-degree
number of outgoing links for each node
degree
total number of incoming and outgoing links for a node
walk
pass among nodes through links
path
only pass different nodes
geodesic
shortest path between two nodes
diameter
largest shortest path between two nodes
average path length
average shortest path between two nodes
clique
everybody is connected to everybody else; fragile and can overlap
weakly connected component
non‐directed path btw every pair
strongly connected component
every node reachable from every other node
structural holes
places where people are unconnected in a network
brokers
actors who exploit structural holes; gain access to information
degree centrality
most connected
-in directed networks: in‐ / out‐degree = # of links incoming / outgoing
Closeness Centrality
closest to all (fewer steps to all others)
-reciprocal of the sum of distances
betweenness centrality
on the paths connecting all
-"gatekeeper", "intermediary" or "broker"
-Sum of shortest paths through node / all shortest path
Girvan-Newman Algorithm
1. Calculate the betweenness of all existing ties
2. Remove the tie with the highest betweenness
3. Recalculate the betweenness of all ties
4. Repeat steps 2 and 3 until no ties remain
quality of partition: modularity
Measuring the density of links
"inside" vs. "between" communities
Eigenvector Centrality
friends of friends
-Proportional to sum of neighbor's centrality
-Google's PageRank: page's rank is proportional to the sum of the rank of linked pages
global measures
Average degree, Degree distribution, path length, etc
local measures
Clustering, transitivity, structural equivalence, etc
individual measures
Degree Centrality, Closeness, Betweenness, Eigenvector, etc.
deduction
reasoning from general to specific
induction
reasoning from specific to general
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