Schema della sezione

  • Introduzione

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  • Additional material

  • R Labs

  • Homeworks

    • Homework 1 Compito
      Aperto: sabato, 23 marzo 2024, 00:00
      Data limite: venerdì, 29 marzo 2024, 23:29

      Solve the exercise in the attached file Homework Fig. 2.4 (from the book by Kolaczyk, 2009, pp. 45-46)

      Please add a text with the solutions and some discussion. 


    • Homework on network descriptive statistics Compito
      Aperto: lunedì, 15 aprile 2024, 00:00
      Data limite: venerdì, 19 aprile 2024, 00:00

      Let consider the following two datasets

      data(aidsblog) and data(yeast) 

      Note that aidsblog is contained in the sand package (so run library(sand) to load it with the command data(aidsblog) ) 

      Yeast is contained in the igraphdata package (so run library(igraphdata) to load it with the command data(yeast) )

      According to the nature of the data:

      1) compute and comment some global network statistics (including size, number of edges, and diameter, please refer for instance to the example of co-authorship in the data collection slides)

      2) if needed decompose the network into distinct components

      3) compute some centrality scores for the individual vertices

      4) extract the ego-network the most central vertex according to at east 2 centrality score (e.g., degree and closeness) and compute and comment the local clustering coefficient 

      Please deliver an R script containing both your code and comments by April 19th possibly.


    • Homework - Network visualization Compito
      Aperto: martedì, 30 aprile 2024, 00:00
      Data limite: martedì, 7 maggio 2024, 01:00

      Considering the fblog data (it's in the "sand" library and it is a snapshot of the network of interactions in a single day of October 2006 among political blogs in France) produce a R file reporting the codes for the following tasks:

      1) produce a graphical representation of the fblog network coloring the nodes according to the political party affiliation

      2) using the same layout of the point 1 (saving as coordinate vectors),  produce a graphical representation of the network where the size of each vertex is proportional to a given centrality measure. Add some comments where you define and explain the chosen centrality measure

      3) plot and comment the degree distribution of the data

      4) plot the network consisting of only those blogs belonging to the most represented political party (the most frequent in the dataset).

      5) choose 2 political parties (say P1 and P2) and plot the network of blogs beloging to the chosen parties using different colors for intra links (P1 <--> P1 and P2 <--> P2) and for interlinks (P1<-->P2)

      Please try to deliver the assignment by May 7th.

    • Homework - Community detection Compito
      Aperto: venerdì, 10 maggio 2024, 00:00
      Data limite: venerdì, 17 maggio 2024, 15:00


      1) Try to use some igraph functions to produce a graph like the caveman graph (see slides on community detection #2)

      Using the graph of the point 1 do the following exercises:

      2) Choose the value k and use the pruning algorithm to detect the cliques of size k (see slides community detection #1, from slides 10 on)

      3) Perform a k-core decomposition and produce the hierarchical plot using the appropriate plot 

      4) obtain the MDS coordinates following the approach from the slides (see community detection #2, slide 7 on)

      5) Compute the initial value of the modularity if all nodes were placed in distinct communities

      6) Run the Louvain algorithm with the built-in igraph function

      7) Implement Newman-Girvan on the same graph and check if you obtain the same solution of the Louvain algorithm

      Please, deliver only the commented R script (no need to upload pictures) possibly by the end of the week.

  • Topic 6

  • Topic 7

  • Topic 8

  • Topic 9

  • Topic 10