这项任务的具体内容是分析网络的各项特性，比如GSCC，degree distribution，centrality 等等。学生需要熟练掌握network相关的python library才能正确地计算出每一个指标。

Part 1

EXERCISE 1.1

Find the Giant Strongly Connected Component (GSCC) for each weekly network. From now on, only use GSCCs for your analysis unless otherwise specified. For each GSCC, compute the following network statistics: 

•  Number of nodes
•  Number of links
•  Density
•  Average clustering coefficient
•  Average degrees (in-degree, out-degree, total degree)
•  Maximum degrees (in-degree, out-degree, total degree)
•  Average strength (in-strength, out-strength, total strength)
•  Average path length
•  Diameter

Display the summary statistics (mean, median, maximum, minimum, standard deviation) of these quantities in a table.

Plot and analyse the total degree distribution for a week of your choice (motivate your choice!). Compare these distributions to those of equivalent networks generated with the following algorithms: Erdős–Rényi, Watts-Strogatz, and Barabasi-Albert. Based on degree distributions and the results you obtained in Exercise 1.1, what type of network would you say the Bitcoin network is? Motivate your answer.

Plot the temporal evolution of the 9 quantities you computed in Exercise 1.1 (for degrees and strengths, only plot the total degree and total strength). Discuss these results in light of the three period of interest (pre-bubble, bubble, after-bubble). Specifically, include comments on:

•  Whether these quantities evolved in the way that you expected, and why.
•  Any signal that might have predicted the bubble.
•  Any significant change during the bubble.
•  Any significant change after the bubble.

Note: Make sure that every plot is clear and it is easy to understand which quantity is being plotted! When discussing the results, be accurate and specify which quantity/plot you are referring to.

Part 2

Using a centrality measure of your choice, find the top ten most important nodes in the network at three different points in time (choose one before, one during, and one after the bubble). Motivate your decisions and justify any assumption you have made. Discuss whether the centrality measure you chose is an accurate measure of the importance of the nodes.

Discuss the role of these nodes in the system (i.e. what do these nodes represent?)

Part 3

Bitcoin exchanges have been targeted by hackers since the beginning of the Bitcoin market. Especially in Bitcoin’s early years, these attacks were quite disruptive (notably, in 2014, consequently to an attack on the then-largest crypto exchange, 7% of all Bitcoins ever created were lost forever). Other attacks caused people to lose millions in Bitcoin and the Bitcoin price to drop significantly. Choose one weekly network and provide an analysis of the network robustness. To do so, you can use the centrality measure you have already computed in Exercise 2.1. Motivate any assumption you have made and discuss the results in detail, including comments on whether it was expected, from a network point of view, that hacker attacks could cause price crashes and major disruption.

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