Muhammad Qasim Pasta

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Social and Information Network Analysis

SINAM

Course DescriptionAnnouncements  | Assignments | Lectures

We are surrounded by networks – network of friendship, network of communication, network of roads are few of such examples. Can we learn anything from these networks? Are all network are similar? Can we answer that which of friend has more influential in network of my friendship? Which road may result extreme traffic jam in city if blocked? How does your position in a social network (dis)advantage you? The answer of these questions related and exists in literature of Network Science.

The emerging field Network Science aims to understand why many networks share these fascinating features and also to investigate what properties consist by these networks in terms of the spread of diseases, routing information, and ranking of the vertices present.

This course will cover computer science topics and other relevant material of field Network Science. The scope of this course is limited to Social and Information Networks as there are many other kind of networks like Biological Networks and Economic Networks.

Course Description: 

Course description is available here.

Announcement:

Assignments

Lectures

Course materials are available at Dropbox Folder

Week 1

Lecture Slides: Lecture01, Lecture1

Reference Material:

Reading Assignment: 

  • Using Organizational Network Analysis to Improve Integration Across Organizational Boundaries, By Dan Novak, Mark Rennaker and Paulette Turner
  • White Paper: SONEAN 

Week 2

Lecture Slides: Lecture02

Reference Material:

  • Chapter #2 (Network Science)

Reading Assignment:

  • Chapter #2 – Book: Network Science (for next Quiz) [Real networks are sparse, Bipartite networks, Connectedness]

Homework:

  • Install Tulip and perform visualization on different datasets available in course material folder.

Resources:

Week 3

Lecture Slides: Lecture03

Reference Material:

  • Chapter #2 (Network Science)

Recommended Reading

  • P. Killworth, C. McCarty, H.R. Bernard, M. House. The accuracy of small-world chains in social networks. Social Networks 28, 85-96, 2006.
  • L. Backstrom, P. Boldi, M. Rosa, J. Ugander, S. Vigna. Four Degrees of Separation. ACM Web Science Conference. 2012.

Homework:

  • You are advised to install R Software(https://www.r-project.org/)  and run basic commands. You can refer "Introduction to R" (available in Reading Assignment of course folder )

Week 4

Lecture Slides: Lecture04, Lecture05

Reference Material:

  • Chapter #3 (Network Science)
  • Introduction to R (slide available in course material folder)

Recommended Reading

  • Erdos, P. & Rényi, A. On the evolution of random graphs Publ. Math. Inst. Hungar. Acad. Sci, Citeseer, 1960, 5, 17-61

Homework:

  • Use datasets available in course material folder and calculate different measures in R as we discussed in class.

Week 5

Lecture Slides: Lecture06

Reference Material:

  • Chapter #3 (Network Analysis)
  • Reference Material for Calculating Clustering Coefficient
  • Reference Material for Calculating Average Path Length

Recommended Reading

  • Newman, M. E. Scientific collaboration networks. I. Network construction and fundamental results Physical review E, APS, 2001, 64, 01613
  • Newman, M. E. Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality Physical review E, APS, 2001, 64, 016132

Week 6

Lecture Slides: Lecture07

Reference Material:

  • Chapter #3 (Network Analysis)

Recommended Reading

  • Bonacich, Phillip. "Power and centrality: A family of measures." American journal of sociology (1987): 1170-1182.
    APA
  • Page, Lawrence, Sergey Brin, Rajeev Motwani, and Terry Winograd. "The PageRank citation ranking: bringing order to the Web." (1999).

Week 7

Lecture Slides: Lecture08, Lecture09

Reference Material:

  • Chapter #2 (Introduction to the Modeling and Analysis of Complex Systems, Hiroki Sayama)

Recommended Reading

  • Watts, D. J. & Strogatz, S. H. Collective dynamics of `small-world' networks, Nature, 1998, 393,
    440-442
  • Barabási, A. L. & Albert, R., Emergence of scaling in random networks, Science, 1999, 286, 509-
    512

Week 8

Lecture Slides: Lecture09

Reference Material:

Reading Assignment

  • Hubs, The meaning of scale-free network (Chapter #4, Network Science)

Recommended Reading

  • Watts, D. J. & Strogatz, S. H. Collective dynamics of `small-world' networks, Nature, 1998, 393,
    440-442
    Barabási, A. L. & Albert, R., Emergence of scaling in random networks, Science, 1999, 286, 509-
    512

Week 9

  • Midter Examination

Week 10

Lecture Slides: None

Reference Material:

  • Handout material available on photocopier shop at city campus

Week 11 & 12

  • Class canceled

Week 13

Lecture Slides: Lecture10

Reference Material:

  • Chapter #9 (Introduction and Basic of Communities)

Week 14

Lecture Slides: Lecture10

Reference Material:

Reading Assignment

  • Overlapping Communities, Testing Communities (Chapter #9, Network Science)

Week 15

Lecture Slides: Lecture11 (Sat Class), Lecture12 (Sun Class)

Reference Material:

  • Chapter #8 (Percolation Theory, Robustness of Scale-free networks, Attack Tolerance)
  • Improving Robustness: Smart rewiring for network robustness Louzada, V. H.; Daolio, F.; Herrmann, H. J. & Tomassini, M., Journal of Complex Networks, Oxford University Press, 2013, 1, 150-159
  • Chapter #10 (Epidemic Modeling, Network Epidemics)
  • R script to simulate random attacks on network

Reading Assignment

  • CASE STUDY: ESTIMATING ROBUSTNESS-   Page# 31, Chapter #8,    Network Science