6th Session- Social Network Analysis 2

This session we deal with the following questions: I. How do networks evolve? II. How can we predict what kind of network will form? III. How can we predict what will happen inside the network?

 

1- Lecture: Watch the following lectures and answer the interactive questions (which are graded). We recommend to use the following slide print-outs to take notes.

1slidePerPage_UCCSS_Lamberson.pdf Download 1slidePerPage_UCCSS_Lamberson.pdf

3slidesPerPage_UCCSS_Lamberson.pdf Download 3slidesPerPage_UCCSS_Lamberson.pdf

UCCSS_Lamberson_1: Influentials (5min) UCCSS_Lamberson_2: Who's influential? (9min) UCCSS_Lamberson_3: Twitter Cascades (8min) UCCSS_Lamberson_4: Base Rate Fallacy (4min) UCCSS_Lamberson_5: Modeling Influentials (7min)

 

1slidePerPage_UCCSS_SNA2_Hilbert-1.pdf Download 1slidePerPage_UCCSS_SNA2_Hilbert-1.pdf

3slidesPerPage_UCCSS_SNA2_Hilbert-1.pdf Download 3slidesPerPage_UCCSS_SNA2_Hilbert-1.pdf

I. How do networks evolve?

UCCSS_SNA2_01: Network Dynamics (9min)

II. How can we predict what kind of network will form?

UCCSS_SNA2_02: Network Hypotheses (5min)

UCCSS_SNA2_03: Random Graphs (6min)

UCCSS_SNA2_04: Tipping Points (8min)

UCCSS_SNA2_05: Scale-free networks (13min)

UCCSS_SNA2_06: Hybrid Models (5min)

UCCSS_SNA2_07: Small World Networks (10min)

UCCSS_SNA2_08: Growing Efficient Networks (18min)

UCCSS_SNA2_09: Growing Stable Networks (8min)

UCCSS_SNA2_10: Efficiency & Stability (3min)

III. How can predict what will happen inside the network?

UCCSS_SNA2_11: Diffusion on Network (6min)

UCCSS_SNA2_12: Diffusion Patterns (6min)

UCCSS_SNA2_13: Computing Networks (3min)

(total 2h 7min)

 

2- No Lab for this session!

 
 

Optional / Voluntary / Complementary: