Introduction

Social Network Analysis: a theory and set of methods focused on the meaning of connections and social structure.

• The point of SNA
  • Relationships, and how we connect with one another, matter!
  • More so than individual traits or characteristics*
  • The way networks are patterned and structured also matters

Important Terms

• Network - A group of individual entities connected in a meaningful way
• Node/Actor/Agent - Individual units
  • People
  • Organizations
  • States
  • Proteins
  • Nuerons
• Edge/Tie/Connection - Defined relationship or connection between nodes
  • Directed or undirected
  • Reciprocal or not

Attributes vs. Relations

• Attributes: What we measure all the time!

  • Income
  • Education
  • Gender
  • Self-efficacy
  • Behavioral variables (e.g., physical activity)

• Relations: ties and structures within networks

  • Who do you know, talk to, trust, spend time with, etc.
  • How closely are you connected to others? How many people are you connected to?
  • Is the network you’re apart of dense, hierarchical, clustered and does that matter?

Basic Assumptions that make SNA different

• Independence is NOT assumed
• Actually, that’s an irresponsible way to think, according to network theory
• “The whole is more than the sum of its parts”
• Nonlinearity
• Inputs and outputs
• Variance explained

Why Might We Need SNA?

• Dissatisfaction with attribute theories of behavior
• “Qualintative”
• More realistic modeling of human behavior
• Behaviors and diseases spread through social contacts, so model that
• Develop better programs/interventions

Why Might We Need SNA?

• It’s SUPER interesting!!
• The field is growing and continues to be “written”
• Applies across physical, biological, and social sciences

Two Approaches to SNA

Egocentric Network Research

• Focuses on personal networks of individual people
• The ego is the “hub” of the network
• Constrained by the environments and activities in which the ego is embedded
• Fits well within standard social/behavioral research

Egocentric Network Measures

• Composition
• Homophily
• Heterogeneity
• Structural Holes

Whole Network Research

• All sets of ties among all members of a given network are studied
• All alters in a whole network are egos, and all egos are alters
• No longer a focal ego
• Allows for individual, group, and network level analysis

Whole Network Measures - Centrality

• A property of a person’s position in a network
• Where does someone “land” in relation to other nodes in a network?
• Central nodes usually carry positions of popularity, power, and prestige
• Centrality typically implies structural importance
• Central nodes often have influence in behavior spread across a network
• Several measures of centrality
  • Degree
  • Betweenness
  • Eigenvector Centrality
  • Closeness

Whole Network Measures - Group-Level

• Subset of a network
• Component (most basic): all nodes that can reach one another through any number of steps; nodes that cannot reach one another are in a separate component of the network
• K-core: subset of the network in which each node is connected to at least K other people
• Creates a density factor for groups
• Clique: all members of a group are connected to all members of that group
• SNA posits that people who engage in a particular behavior are often surrounded by other people who also engage in that behavior, or at least approve of doing so

Whole Network Measures - Network-Level

• Calculated on the whole network (as opposed to each node)
• Investigates the network from a global (or bird’s eye) perspective
• Density
• Centralization
• Average path length
• Density and Centralization