Network Analysis in the Tidyverse

The challenge in this chapter is to spot the most highly connected terrorists in the network. We will first import the dataset and build the network. Then we will learn how to visualize it in different layouts using ggraph package. Later on, we will compute two basic yet important centrality measures in network science - degree and strength. We will use them to spot highly connected terrorists. We will finally touch two alternative centrality measures, betweenness and closeness.

In this chapter we will spot the most influential ties among terrorists in the network. We will use a centrality measure on ties, called betweenness, and will learn how to visualize the network highlighting connections with high betweenness centrality. Moreover, we will provide some alternative evidence regarding Mark Granovetter's theory of strength of weak ties, confirming that looser connections are crucial as demonstrated in the Madrid terrorism network.

The challenge in this chapter is to discover pairs of similar (and dissimilar) terrorists. We will introduce the adjacency matrix as a mathematical representation of a network and use it to find terrorists with similar connection patterns. We will also learn how to visualize similar and dissimilar pairs of individuals using ggraph.

In this chapter we will discover cells of similar terrorists. We will explore hierarchical clustering to find groups of similar terrorists building on the notion of similarity of connection patterns developed in the previous chapter. Furthermore, we will explore the visNetwork package to produce fulfilling interactive network visualizations.