Handouts

0 - The Network Science Course

• Slides:
  • Information about the course

1 - Fundamentals of Network Science

• Slides:
  • An introduction to Network Science
• Other Material:
  • Network Science - Chapter 1: Introduction (A. Barabasi)
  • Network Science - Chapter 2: Graph Theory (A. Barabasi)
  • Networks, Crowds and Markets - Chapter 1: Overview (D. Easley and J. Kleinberg)
  • Networks, Crowds and Markets - Chapter 2: Graphs (D. Easley and J. Kleinberg)
  • The "new" science of networks (D. Watts)

2 - Graph Models

• Slides:
  • Graph Models and Random Networks (selected slides from J. Leskovec and L. Adamic)
• Other Material:
  • Network Science - Chapter 3: Random Networks (A. Barabasi)
  • Network Science - Chapter 4: The Scale-Free Property (A. Barabasi)
  • Network Science - Chapter 5: The Barabasi-Albert Model (A. Barabasi)
  • Networks, Crowds and Markets - Chapter 18: Power Laws and Rich-Get-Richer Phenomena (D. Easley and J. Kleinberg)
  • Networks, Crowds and Markets - Chapter 20: The Small-World Phenomenon (D. Easley and J. Kleinberg)

3 - Centrality

• Slides:
  • Node Centrality (selected slides from J. Leskovec and L. Adamic)
• Other Material:
  • Centrality Measures and Link Analysis (G. Mateos)
  • Wikipedia: Centrality

4 - Link Analysis

• Slides:
  • Link Analysis (selected slides from J. Leskovec and L. Adamic)
• Other Material:
  • Centrality Measures and Link Analysis (G. Mateos)
  • Wikipedia: HITS algorithm
  • Wikipedia: PageRank

5 - Community Structure in Networks

• Slides:
  • Community Structure in Networks (selected slides from J. Leskovec)
• Other Material:
  • Network Science - Chapter 9: Communities (A. Barabasi)
  • Networks, Crowds and Markets - Chapter 3: Strong and Weak Ties (D. Easley and J. Kleinberg)
  • Network Community Detection (G. Mateos)

6 - Subgraph Patterms

• Slides:
  • Subgraphs as Fundamental Ingredients of Complex Networks
• Other Material:
  • gtrieScanner (P. Ribeiro)
  • Some articles to read:
  • Network motifs: simple building blocks of complex networks (Milo et al, 2002)
  • Superfamilies of evolved and designed networks (Milo et al, 2004)
  • Biological network comparison using graphlet degree distribution (N Przulj, 2018)
  • G-Tries: a data structure for storing and finding subgraphs (Ribeiro and Silva, 2014) [pre-print version]

7 - Diffusion and Cascading Behavior

• Slides:
  • Diffusion and Cascading Behavior - Part 1 (Decision Based Models) (selected slides from J. Leskovec)
  • Diffusion and Cascading Behavior - Part 2 (Probabilistic Models) (selected slides from J. Leskovec)
• Other Material:
  • Reproductive Number
    • Basic Reproductive Number (Wikipedia)
    • Liu, Y., Gayle, A. A., Wilder-Smith, A., & Rocklöv, J. (2020). The reproductive number of COVID-19 is higher compared to SARS coronavirus. Journal of travel medicine.
  • Epidemic Models
    • Compartmental Models in Epidemiology (Wikipedia)
    • SIR Model (Hans Nesse, Arizona State University)
    • Epidemix - Visually Explore Disease Transmission (University of London)
    • Epidemic Calculator for COVID-19
    • What Happens Next? COVID-19: Futures, Explained With Playable Simulations (M. Salathé, epidemiologist & N. Case, art/code)
    • Gomes, M. F., y Piontti, A. P., Rossi, L., Chao, D., Longini, I., Halloran, M. E., & Vespignani, A. (2014). Assessing the international spreading risk associated with the 2014 West African Ebola outbreak. PLoS currents, 6.
    • Althaus, C. L. (2014). Estimating the reproduction number of Ebola virus (EBOV) during the 2014 outbreak in West Africa. PLoS currents, 6.
  • Data and general resources for COVID-19
    • The Coronavirus Tech Handbook
    • COVID-19 Data Repository (Johns Hopkins University) [includes times series for all countries]
    • Dados relativos à pandemia COVID-19 em Portugal (Data Science for Social Good Portugal)

8 - Network Construction

• Slides:
  • Network Construction (selected slides from J. Leskovec and L. Lacasa)
• Other Material:
  • (to be added)

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