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Strong and Weak Ties (Measures (Neighbourhood Overlap
number of nodes…
Strong and Weak Ties
Measures
The Clustering Coefficient
- coefficient for every node between 0 and 1
- pairs of neighbours wich are connected to each other divided by the number of pairs of neighbours
Neighbourhood Overlap
- number of nodes who are friends of both A and B divided by
- number of nodes who are friends of at least one of A and B
- between 0 and 1
- 0 leads to local bridge
Dependencies
- overlap grows as tie strength grows
- giant components shrank more rapidly, breaks apart when critical number of weak ties is removed
Embeddedness
- measure of an edge
- number of nodes the endpoints of the edge have in common
- equal to the numerator of Neighbourhood Overlap
- local bridge = 0
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Triadic Closure
- two nodes A and B which are connected two a node C, are more likely to be connected in the future with each other
- the triangle is created or closed
Reasons
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- trust in each other because of same friend
- A wants B and C to be friends, otherwise stress through different friend groups
The Strong Triadic Closure Property
- edges between two nodes can be classified into strong and weak ties
- more likely an edge between C and B if A is connected to them with strong edges
- this rule gets violated if A has strong ties to C and B, but they dont have a conncetion
Properties
- if a node A fulfills STCP and has two strong ties, any involved local bridge is a weak tie
- leads to local bridge = weak tie often
Tie Strength, Social Media and Passvie Engagement
- friends in social media can be classified into strong and weak ties
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Active Network Size
- even accounts with many friends (over 500), only communicate with 10 or 20 and follow passively under 50 friends
Changing communication patterns
- big contrast between reciprocal and passive network shows the effect of technologies as News feed
- events spread rapidly through passive network
- communication via phone would lead to small network
- Impact of technology on communication pattern
Closure and Structural Holes
- some nodes only have acces to boundary spanning edges
- some nodes are positioned in the middle of a single group
Bridges
- an edge is a Bridge if deleting this edge leads to creating two components in the graph out of one single component
- very rare through giant component
Local Bridge
- an edge is a bridge if its endpoints (nodes) have no friends in common
- this leads to a greater distance than 2
- an edge is a local bridge if not part of a triangle (Triadic Closure)
Span of local bridge
- distance of to nodes if the local bridge gets deleted
Structural Holes
- nodes at the end of multiple local bridges can have advantages
- information interface
- success of manager is higher with access to local bridges
- can span a structural hole in the organization
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Social Capital
bonding capital
- arrising from connection within a tightly-knit group
bridging-capital
- arrising from conncetions between groups