Handouts
1 - Fundamentals of Network Science
- Videos:
- Slides:
- Other Material:
2 - Measuring Networks and Random Graph Models
- Videos:
- Slides:
- 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)
- NetLogo Visualizations:
- Some papers mentioned in lectures:
- Leskovec, J., & Horvitz, E. (2008, April). Planetary-scale views on a large instant-messaging network. In Proceedings of the 17th international conference on World Wide Web (pp. 915-924).
- Erdős, P., & Rényi, A. (1960). On the evolution of random graphs. Publ. Math. Inst. Hung. Acad. Sci, 5(1), 17-60.
- Travers, J., & Milgram, S. (1969). An experimental study of the small world problem. Sociometry, 32(4), 452-443.
- Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of ‘small-world’networks. Nature, 393(6684), 440-442.
- Barabási, A. L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439), 509-512.
- Clauset, A., Shalizi, C. R., & Newman, M. E. (2009). Power-law distributions in empirical data. SIAM review, 51(4), 661-703.
3 - Centrality
- Videos:
- Slides:
- Other Material:
4 - Link Analysis
- Videos:
- Slides:
- Other Material:
- Centrality Measures and Link Analysis (G. Mateos)
- Wikipedia: HITS algorithm
- Wikipedia: PageRank
- NetLogo Visualizations:
- Some papers mentioned in lectures:
- Broder, A., Kumar, R., ... & Wiener, J. (2000). Graph structure in the web. Computer networks, 33(1-6), 309-320.
- Kleinberg, J. M. (1999). Authoritative sources in a hyperlinked environment. Journal of the ACM (JACM), 46(5), 604-632.
- Page, L., Brin, S., Motwani, R., & Winograd, T. (1999). The PageRank citation ranking: Bringing order to the web. Stanford InfoLab.
5 - Roles and Community Structure in Networks
- Videos:
- Slides:
- 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)
- Some papers mentioned in lectures:
- Fortunato, S. (2010). Community detection in graphs. Physics reports, 486(3-5), 75-174.
- Fortunato, S., & Hric, D. (2016). Community detection in networks: A user guide. Physics reports, 659, 1-44.
- Blondel, V. D., Guillaume, J. L., Lambiotte, R., & Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of statistical mechanics: theory and experiment, 2008(10), P10008. [Louvain Algorithm]
6 - Subgraph Patterms
- Videos:
- Slides:
- Other Material:
- gtrieScanner (P. Ribeiro)
- Some articles to read:
- Milo, R., Shen-Orr, S., Itzkovitz, S., Kashtan, N., Chklovskii, D., & Alon, U. (2002). Network motifs: simple building blocks of complex networks. Science, 298(5594), 824-827.
- Milo, R., Itzkovitz, S., Kashtan, N., Levitt, R., Shen-Orr, S., Ayzenshtat, I., ... & Alon, U. (2004). Superfamilies of evolved and designed networks. Science, 303(5663), 1538-1542.
- Pržulj, N. (2007). Biological network comparison using graphlet degree distribution. Bioinformatics, 23(2), e177-e183.
- Ribeiro, P., & Silva, F. (2014). G-tries: a data structure for storing and finding subgraphs. Data Mining and Knowledge Discovery, 28(2), 337-377. [pre-print version]
- Ribeiro, P., Paredes, P., Silva, M. E., Aparicio, D., & Silva, F. (2021). A Survey on Subgraph Counting: Concepts, Algorithms, and Applications to Network Motifs and Graphlets. ACM Computing Surveys (CSUR), 54(2), 1-36.
7 - Diffusion and Cascading Behavior
- Videos:
- Slides:
- Other Material:
- Reproductive Number
- Epidemic Models
- Compartmental Models in Epidemiology (Wikipedia)
- The Mathematics of Epidemicsl (Alan Zucconi)
- 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