Editing Social network analysis (section)

==Metrics==
Size: The number of network members in a given network.

===Connections===
[[Homophily]]: The extent to which actors form ties with similar versus dissimilar others. Similarity can be defined by gender, race, age, occupation, educational achievement, status, values or any other salient characteristic.<ref>{{cite journal |last1=McPherson |first1=Miller |last2=Smith-Lovin |first2=Lynn |last3=Cook |first3=James M |title=Birds of a Feather: Homophily in Social Networks |journal=Annual Review of Sociology |date=August 2001 |volume=27 |issue=1 |pages=415–444 |doi=10.1146/annurev.soc.27.1.415 |s2cid=2341021 }}</ref> Homophily is also referred to as [[assortativity]].

Multiplexity: The number of content-forms contained in a tie.<ref name = "Podo97"/> For example, two people who are friends and also work together would have a multiplexity of 2.<ref>{{cite book |author1=Kilduff, M.|author2=Tsai, W. |year=2003 |title= Social networks and organisations |publisher=Sage Publications}}</ref> Multiplexity has been associated with relationship strength and can also comprise overlap of positive and negative network ties.<ref name=Brennecke2019>{{cite journal |last1=Brennecke |first1=Julia |title=Dissonant Ties in Intraorganizational Networks: Why Individuals Seek Problem-Solving Assistance from Difficult Colleagues |journal=Academy of Management Journal |date=June 2020 |volume=63 |issue=3 |pages=743–778 |doi=10.5465/amj.2017.0399 |s2cid=164852065 |oclc=8163488129 }}</ref>

Mutuality/Reciprocity: The extent to which two actors reciprocate each other's friendship or other interaction.<ref name="Kadu12"/>

[[Triadic closure|Network Closure]]: A measure of the completeness of relational triads. An individual's assumption of network closure (i.e. that their friends are also friends) is called transitivity. Transitivity is an outcome of the individual or situational trait of [[Closure (psychology)|Need for Cognitive Closure]].<ref name="Flyn10"/>

[[Propinquity]]: The tendency for actors to have more ties with geographically close others.

===Distributions===
[[Bridge (graph theory)|Bridge]]: An individual whose weak ties fill a [[Structural holes|structural hole]], providing the only link between two individuals or clusters. It also includes the shortest route when a longer one is unfeasible due to a high risk of message distortion or delivery failure.<ref name="Granovetter, M. 1973 1360–1380">{{cite journal |last1=Granovetter |first1=Mark S. |title=The Strength of Weak Ties |journal=American Journal of Sociology |date=May 1973 |volume=78 |issue=6 |pages=1360–1380 |doi=10.1086/225469 |s2cid=59578641 }}</ref>

[[Centrality]]: Centrality refers to a group of metrics that aim to quantify the "importance" or "influence" (in a variety of senses) of a particular node (or group) within a network.<ref>{{cite book|author=Hansen, Derek|title=Analyzing Social Media Networks with NodeXL|publisher=Morgan Kaufmann|year=2010|isbn=978-0-12-382229-1|page=32|url=https://books.google.com/books?id=rbxPm93PRY8C&pg=PA32|display-authors=etal}}</ref><ref>{{cite book|author=Liu, Bing|title=Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data|publisher=Springer|year=2011|isbn=978-3-642-19459-7|page=271|url=https://books.google.com/books?id=jnCi0Cq1YVkC&pg=PA271}}</ref><ref>{{cite book|author=Hanneman, Robert A.|author2=Riddle, Mark|name-list-style=amp|chapter=Concepts and Measures for Basic Network Analysis|title=The Sage Handbook of Social Network Analysis|publisher=SAGE|year=2011|isbn=978-1-84787-395-8|pages=364–367|chapter-url=https://books.google.com/books?id=2chSmLzClXgC&pg=PA364}}</ref><ref>{{cite book|author1=Tsvetovat, Maksim |author2=Kouznetsov, Alexander|name-list-style=amp|title=Social Network Analysis for Startups: Finding Connections on the Social Web|publisher=O'Reilly|year=2011|isbn=978-1-4493-1762-1|page=45|url=https://books.google.com/books?id=hVOxjkoLSiEC&pg=PA45}}</ref>  Examples of common methods of measuring "centrality" include [[betweenness centrality]],<ref name="comprehensive"/> [[closeness centrality]], [[eigenvector centrality]], [[alpha centrality]], and [[degree centrality]].<ref>{{cite journal |last1=Opsahl |first1=Tore |last2=Agneessens |first2=Filip |last3=Skvoretz |first3=John |title=Node centrality in weighted networks: Generalizing degree and shortest paths |journal=Social Networks |date=July 2010 |volume=32 |issue=3 |pages=245–251 |doi=10.1016/j.socnet.2010.03.006 }}</ref>

[[Dense graph|Density]]: The proportion of direct ties in a network relative to the total number possible.<ref>{{cite book|chapter=Social Network Analysis|title=Field Manual 3-24: Counterinsurgency|publisher=Headquarters, [[Department of the Army]]|pages=B–11 – B–12|chapter-url=https://fas.org/irp/doddir/army/fm3-24.pdf}}</ref><ref>{{cite book|author=Xu, Guandong |title=Web Mining and Social Networking: Techniques and Applications|publisher=Springer|year=2010|isbn=978-1-4419-7734-2|page=25|url=https://books.google.com/books?id=mXo9zKeYa6cC&pg=PA25|display-authors=etal}}</ref>

Distance: The minimum number of ties required to connect two particular actors, as popularized by [[Stanley Milgram]]'s [[small world experiment]] and the idea of 'six degrees of separation'.

Structural holes: The absence of ties between two parts of a network.  Finding and exploiting a structural hole can give an [[entrepreneur]] a competitive advantage.  This concept was developed by sociologist [[Ronald Stuart Burt|Ronald Burt]], and is sometimes referred to as an alternate conception of social capital.

Tie Strength: Defined by the linear combination of time, emotional intensity, intimacy and reciprocity (i.e. mutuality).<ref name="Granovetter, M. 1973 1360–1380"/> Strong ties are associated with homophily, propinquity and transitivity, while weak ties are associated with bridges.

===Segmentation===
Groups are identified as '[[clique]]s' if every individual is directly tied to every other individual, '[[social circle]]s' if there is less stringency of direct contact, which is imprecise, or as [[Structural cohesion|structurally cohesive]] blocks if precision is wanted.<ref name="uci"/>

[[Clustering coefficient]]: A measure of the likelihood that two associates of a node are associates. A higher clustering coefficient indicates a greater 'cliquishness'.<ref>{{cite book|author=Hanneman, Robert A.|author2=Riddle, Mark|name-list-style=amp|chapter=Concepts and Measures for Basic Network Analysis|title=The Sage Handbook of Social Network Analysis|publisher=SAGE|year=2011|isbn=978-1-84787-395-8|pages=346–347|chapter-url=https://books.google.com/books?id=2chSmLzClXgC&pg=PA346}}</ref>

Cohesion: The degree to which actors are connected directly to each other by [[Social cohesion|cohesive bonds]]. [[Structural cohesion]] refers to the minimum number of members who, if removed from a group, would disconnect the group.<ref name="asanet"/><ref>{{cite book|author=Pattillo, Jeffrey|chapter=Clique relaxation models in social network analysis|editor1=Thai, My T.|editor2=Pardalos, Panos M.|name-list-style=amp|title=Handbook of Optimization in Complex Networks: Communication and Social Networks|publisher=Springer|year=2011|isbn=978-1-4614-0856-7|page=149|chapter-url=https://books.google.com/books?id=bdRdcHxQQLQC&pg=PA149|display-authors=etal}}</ref>