An Introduction to Social Network Analysis (SNA) in R

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# An Introduction to Social Network Analysis (SNA) in R
## CORE Lab
### Department of Defense Analysis
### 2019-08-08

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# Introduction

* Purpose

* Scope

* SNA in R

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# What are social networks?

* We emphasize the *social* in social networks.
  
--

* Online and offline social networks

.center[
![](online_offline.png)]

---

# What is social network analysis?

* SNA is a set of theories and techniques used to understand social structures.

* We use SNA to identify strengths and vulnerabilities in social networks.

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# Social Network Example

* Person A is a member of Gang X and lives in Neighborhood 1. He has admittedly sold drugs to two individuals who reside in Neighborhood 1, Person D (male) and Person E (female). Person A is the brother of Person C and has two sisters, Actors F and G (both live in Neighborhood 2). Person A was arrested in the past with Person H (a close friend of B) and Person I.

* Person B's affiliation is unknown and he lives in Neighborhood 3. Person B communicates with Persons F, G, and J.  She is a friend of Person C, Person J (Gang X), and  Person L.  She lied to police about Person C's whereabouts on the night of a shooting last year. Person B hangs out with F, who knows L and N.

* Person C is also a member of Gang X and lives in Neighborhood 2.Person H (Neighborhood 2), looks up to Person C.  Person C's close friend, Person I (Neighborhood 2), is dating Person G and Person C communicates with Person J (Neighborhood 3).

* Person D is a member of Gang Y and lives in Neighborhood 1.Person D regularly communicates with Person K ( member of Gang Z) and Person L.

* Person E's affiliation is unknown. She is a close friend of Person K (Neighborhood 1) and is suspected of being a drug dealer.  She dated Person K and Person A, and she hangs out with Person L (affiliation unknown) and Person M (affiliation unknown) from Neighborhood 1.

---

# Social Network Example

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# Social Network Example

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# Social Network Example

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# Social Network Example

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---

# Common Misconceptions

* Several misconceptions exist, but two appear to be the most prevalent.

* SNA vs. Link Analysis

* SNA vs. Social Media Analysis

---

# Approach

* Network Topography

* Cohesive Subgroups

* Centrality

* Brokers and Bridges

* Roles and Positions

--
* Confirmatory SNA
  * Conditional Uniform Graph (CUG) Test
  * Quadratic Assignment Procedue (QAP) Test
  * Exponential Random Graph Models (ERGMs)
  * Stochastic Actor Oriented Models (SAOMs)

---

# Centrality

|**Measure** | **Definition** | **Interpretation** | **Caveat** |
|-----------|-------------------| -------------------------|-----------------------|
|**Degree** (frequency)| Count of an actor's ties. | Actor activity; Direct power or influence, or ability to be influenced by others | In some cases, well-connected actors are the result of biased connections. |
|**Eigenvector** (frequency) | Weights an actor's degree centrality by the degree centrality of its neighbors. | Indirect influence or power; Potential social capital. | In well-connected networks, it is often difficult to identify a single, or a few, potentially powerful actors. |
|**Betweenness** (paths) | How often each actor lies on the shortest path between all pairs of actors. | Brokerage potential; Gatekeepers; Boundary Spanners | Betweenness assumes a desire for efficiency. Actors, resources, and information may not always follow shortest paths. | 
|**Closeness** (distance) | The average shortest path (i.e., geodesic) distance from an actor to every other actor in the network. | Actor levels of accessibility to others, and to material and non- material goods. | Not designed for use with disconnected networks.

---

# Hypothetical Network (Offline)

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# Hypothetical Network (Offline)

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# Attribute Table (Gang Network Top-5 Eigenvector)

|**Rank**  | **Name**  | **Affiliation**  | **Other Gang Connections**  | **Crime Type**
|---------|-------------| ----------------|--------------|------------|
|1| O.G. (1)| County Boys | Almighty Angels,Blood Army, Guerrilla Posse, & 21st St.   | Narcotic Offenses |
|2| Fat Boy (.07) | Almighty Angels | County Boys | Burglary |
|3| Freckles (.65)| Unknown | Almighty Angels & 21st St. | None |
|4|  Boots (.62) | Unknown | Almighty Angels |None |
|5|  2 Tied at .56 |  N/A | N/A | N/A |

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# Questions?

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Dan Cunningham - dtcunnin@nps.edu