Syllabus Outakes

Network Perspectives in "Old" Social Science

See also
Wellman, Barry. "Structural Analysis: From Metaphor to Substance," pp. 19-48 in Wellman & Berkowitz: Social Structures: A Network Approach.
Hanneman Lecture Outline
Watts, ch 1 "The Connected Age" (23)
Watts, ch 2 "The Origins of a 'New Science'" (25)

The New Science of Networks

Connection: Ego neighborhoods (RH)

Opportunity and constraint; holes and embedding

social support, strength of weak ties, neighborhood, bureaucracies, Density, Clustering, Competition, boundaries, Brokerage

Hanneman and Riddle 8 (except section on Krackhardt)

Network Theories of Power

Feb. 20, 2010: Network Theories of Power David Grewal, Harvard University at USC Annenberg

Social networks are not random (RH)

Watts 3.

Making connections: Social contexts: Affiliation and identity (RH)

Hierarchy, efficiency, and robustness (RH)

Differentiation and integration; specialization and coordination; Evolutionary selection; Reliability/vulnerability; Markets and their failures; Hierarchy and its failures; Beyond markets and hierarchies; Government: organized coercion and coordination; Cultural production/art; Health/education/welfare

Hanneman and Riddle ch 8, section on Krackhardt
Watts 9.
  1. A Fun Introduction and Overview


  1. Basic Concepts
    1. nodes/edges (and alternative nomenclature)
    2. directed/undirected/weighted/unweighted
    3. notation
    4. graphs
    5. adjacency matrix
      1. rows, columns, notation, interpretation
  2. Mathematical Tools
    1. subscripts
    2. ordered pairs
    3. matrix
    4. summation
    5. "sumproduct"
  3. Social Media and Social Networks
  4. Centrality
  5. Connectedness
  6. Clustering
  7. Organizations (intra- and inter-)
  8. Data collection
  9. Visualization

Thinking about the world in network terms

Adventures in Networks
Math Prerequisites
Software introduction

Basics Network Visualization
25‐Jan Basics When images do not suffice: Network
analytical measures
HW 1 out
27‐Jan Networks: Structures, Models,
Models and Simulation of Network Evolution
1‐Feb Networks: Structures, Models,
Models and Simulation of Network Evolution
3‐Feb Networks: Structures, Models,
Models and Simulation of Diffusion in
Groups Subgroups and Cliques
10‐Feb Groups Clustering HW 2 due
15‐Feb Groups Block models HW 3 out
17‐Feb Dyads and Individuals Ego networks
22‐Feb Dyads and Individuals Reciprocity HW 3 due, HW 4 out
24‐Feb Dyads and Individuals Social capital, structural holes, equivalence

Ethics and Privacy HW 5 (project) out,
project data out
17‐Mar Data collection Manual and ethnographic methods,
automated methods
22‐Mar Data collection Cognitive Social Structures

Milgram small world; terrorists; amazon books you like; Itunes genius
Mathematical Foundations
Networks and Kinship

0 R Sept. 29 Introduction: Networks everywhere First data collection
1 T Oct. 4 The social networks perspective I Watts 1.
1 R Oct. 6 The social networks perspective II Watts 2.
2 T Oct. 11 Social network data and methods Hanneman and Riddle 1, 2, 6.
2 R Oct. 13 Graphs and Matrices Hanneman and Riddle 3, 4, 5.
3 T Oct. 18 Basic measures for individuals and networks Hanneman and Riddle 7.
3 R Oct. 20 Midterm 1 Second data collection
4 T Oct. 25 Making connections: Random graphs and network evolution Watts 3.
4 R Oct. 27 Making connections: Social contexts: Affiliation and identity Watts 4.
5 T Nov. 1 Connection: Search, collapse, robustness Watts 5, 6.
5 R Nov. 3 Connection: Social movements and diffusion of innovation Watts 7, 8.
6 T Nov. 8 Connection: Ego neighborhoods Hanneman and Riddle 8 (except section on Krackhardt, 9.
6 R Nov. 10 Connection: Ego neighborhoods (cont.)
7 T Nov. 15 Midterm 2 Third data collection
7 R Nov. 17 Centrality, centralization, and power Hanneman and Riddle 10.
8 T Nov. 22 Hierarchy, efficiency, and robustness Hanneman and Riddle 8, section on Krackhardt; Watts 9.
9 T Nov. 29 Cliques and groups Hanneman and Riddle 11.
9 R Dec. 1 Homophily and social segregation
10 T Dec. 6 Equivalence: Positions Hanneman and Riddle 12, 13.
10 R Dec. 8 Equivalence: Social Roles
Hanneman and Riddle, 15.
Term paper is due at lecture

Exam T Dec. 13
8:00-11:00am Final exam

Studying Networks in the lab

  1. Centola, D. 2010. "The Spread of Behavior in an Online Social Network Experiment." Science 329: 1194-7. []
  2. Brañas-Garza, Pablo, Ramón Cobo-Reyes, María Paz Espinosa, Natalia Jiménez, Jaromír Kovářík and Giovanni Ponti (2010): Altruism and Social Integration. Games and Economic Behavior 69(2): 249-257. []
  3. Kittel, Bernhard and Wolfgang Luhan (2011): Decision Making in Networks. An Experiment on Structure Effects in a Group Dictator Game, Social Choice and Welfare, Online First, 15 September 2011. []
  4. Goldstone, R. L., Roberts, M. E., & Gureckis, T. M. (2008). Emergent Processes in Group Behavior. Current Directions in Psychological Science, 17, 10-15.
  5. Kosfeld, M. Economic Networks in the Laboratory: A Survey Review of Network Economics, 2004, 3, 20-41
  6. Martijn J. Burger, Vincent Buskens, Social context and network formation: An experimental study, Social Networks, Volume 31, Issue 1, January 2009
  7. Rense Corten, Vincent Buskens, Co-evolution of conventions and networks: An experimental study, Social Networks, Volume 32, Issue 1, January 2010
  8. Bavelas, A., 1950. Communication Patterns in Task-Oriented Groups. The Journal of Acoustical Society of America 22, 271-282.
  9. Guetzkow, H., Simon, H.A., 1955. The Impact of Certain Communication Nets Upon Organization and Performance in Task-Oriented Groups. Management Science 1, 233-250.
  10. Leavitt, H.J., 1951. Some effects of certain communication patterns on group performance. Journal of Abnormal and Social Psychology 46, 38-50.

Background, definitions, etc

  • Scott: 1-37.
  • Stanley Wasserman and Katherine Faust. 1994. Social Network Analysis: Methods and


  • Mark Granovetter. 1973. “Th
  • Structural holes

Handling and visualizing network dat


Small worlds

Network origin

Social Capital

Diffusion and social influence

Knowledge network
Intra-organizational network

Applying SN tools within an organization

Inter-organizational networks