Q1. The Marvel network data contains character relationships within the Marvel comic book universe (beginning in 1961 and ending around 1999/2000), compiled by Rossell, Alberich, and Miro from Russ Chappell's from Russ Chappell's Marvel Chronology Project.

-use marvel-unimodal-edges.csv in the marvel folder -load the data as a graph object in igraph -add edge weights as an edge attribute -plot the network

```{r} # Write your code here

```

Q2. Obtain the degree distribution of the marvel network; plot the network's degree distribution and calculate the degree centralization of the network. What can you conclude?(Answer the last question in a sentence starting with # to comment it off)

```{r} # Write your code here

```

Q3. Which nodes(s) are most central in the network in terms of degree, closeness, betweenness and eigenvector centrality? What can you conclude? (Answer the last question in a sentence starting with # to comment it off)

```{r} # Write your code here

```

Q4. Calculate the density, clustering and average path lengths of the network. What can you conclude? (Answer the last question in a sentence starting with # to comment it off)

```{r} # Write your code here

```

Q5. Compare the Marvel network to a random network with the same size and density. What can you conclude? (Answer the last question in a sentence starting with # to comment it off) (Hint: simulate a random network and compare its clustering and transitivity with the Marvel network)

```{r echo = T} # Write your code here

Need answers in "R" programming language. questions are from "social networking analysis".