Social Architect

Notes, sketches, links and thoughts re: Online Community, Social Media, Online Strategy

Notes & reading list from the Social Network Analysis Workshop

Marc Smith (@Marc_Smith) of Connected Action ran his Social Network Analysis workshop yesterday. 

Below are my raw notes, links and key items (mostly cribbed from Wikipedia).

Marc started by showing us the first image of the earth, transmitted from Tiros 1 on April 1, 1960

Media_httpuploadwikimediaorgwikipediacommonsee8tiros1earthpng_vqnhjbfndpccfxj

He made the point that we are at a similar moment with social graph data - just beginning to harvest, visualize and understand.

Social Network Analysis 101

Select Measurements & Definitions
http://en.wikipedia.org/wiki/Social_network_analysis#Metrics_.28Measures.29_in_social_network_analysis

Betweenness
The extent to which a node lies between other nodes in the network. This measure takes into account the connectivity of the node's neighbors, giving a higher value for nodes which bridge clusters. The measure reflects the number of people who a person is connecting indirectly through their direct links.[19]
Bridge
An edge is said to be a bridge if deleting it would cause its endpoints to lie in different components of a graph.
Centrality
This measure gives a rough indication of the social power of a node based on how well they "connect" the network. "Betweenness", "Closeness", and "Degree" are all measures of centrality.
Centralization
The difference between the number of links for each node divided by maximum possible sum of differences. A centralized network will have many of its links dispersed around one or a few nodes, while a decentralized network is one in which there is little variation between the number of links each node possesses.
Closeness
The degree an individual is near all other individuals in a network (directly or indirectly). It reflects the ability to access information through the "grapevine" of network members. Thus, closeness is the inverse of the sum of the shortest distances between each individual and every other person in the network. (See also: Proxemics)
Clustering coefficient
A measure of the likelihood that two associates of a node are associates themselves. A higher clustering coefficient indicates a greater 'cliquishness'.
Cohesion
The degree to which actors are connected directly to each other by cohesive bonds. Groups are identified as ‘cliques’ if every individual is directly tied to every other individual, ‘social circles’ if there is less stringency of direct contact, which is imprecise, or as structurally cohesive blocks if precision is wanted.[20]
Degree
The count of the number of ties to other actors in the network. This may also be known as the "geodesic distance". See also degree (graph theory).
(Individual-level) Density
The degree a respondent's ties know one another/ proportion of ties among an individual's nominees. Network or global-level density is the proportion of ties in a network relative to the total number possible (sparse versus dense networks).
Eigenvector centrality
A measure of the importance of a node in a network. It assigns relative scores to all nodes in the network based on the principle that connections to nodes having a high score contribute more to the score of the node in question.
Local Bridge
An edge is a local bridge if its endpoints share no common neighbors. Unlike a bridge, a local bridge is contained in a cycle.
Path Length
The distances between pairs of nodes in the network. Average path-length is the average of these distances between all pairs of nodes.
Reach
The degree any member of a network can reach other members of the network.
Structural cohesion
The minimum number of members who, if removed from a group, would disconnect the group.[21]
Structural equivalence
Refers to the extent to which nodes have a common set of linkages to other nodes in the system. The nodes don’t need to have any ties to each other to be structurally equivalent.

Seven Bridges of Königsberg

Social Network Analysis Tools:

Google's SNA API

Elinor Ostrom's Eight Design Principles of Common Pool Resource Management
http://en.wikipedia.org/wiki/Elinor_Ostrom
Ostrom identifies eight "design principles" of stable local common pool resource management:[4]

 

  1. Clearly defined boundaries (effective exclusion of external unentitled parties);
  2. Rules regarding the appropriation and provision of common resources are adapted to local conditions;
  3. Collective-choice arrangements allow most resource appropriators to participate in the decision-making process;
  4. Effective monitoring by monitors who are part of or accountable to the appropriators;
  5. There is a scale of graduated sanctions for resource appropriators who violate community rules;
  6. Mechanisms of conflict resolution are cheap and of easy access;
  7. The self-determination of the community is recognized by higher-level authorities;
  8. In the case of larger common-pool resources: organization in the form of multiple layers of nested enterprises, with small local CPRs at the base level.

 

Expanding the Dunbar Number
http://en.wikipedia.org/wiki/Dunbar_number

"Dunbar's number is a theoretical cognitive limit to the number of people with whom one can maintain stable social relationships."

  • Grounded by carrying capacity of land / tribes

Now eDunbar number- 150 augmented by crutches – recall vs. stimulus / response

Augmented social relationships – strong ties stable, weak ties growing.

Strength of Weak Ties