Thumbs Up Will Be Given For Answer.

A) Fill in the Blanks in the table below from the information in Chapter 14 of the course pack and fill out the missing information in each column (in the first column, fill in the missing name of the definition in the second column, while in the second column, fill in the missing definition that matches network property/component in the first column.) Example Network Property Component Structural Holes The Cyber Research case study compares the average degree of the Korean vs. the US ministries on Twitter and concludes that was higher for the Korean network (0.86) than for the U.S. network (0.50), indicating that the Korean network was more likely to form "cliques." Density In a Facebook network, for example, degree centrality will measure the number of mutual friends that a member has (great for influence measurement.) Diameter In most social networks, larger nodes are often calculated and represented as more important due to Eigenvector calculations (often due to a variety of weightings combined the calculation is beyond the scope of this book.) Google Search also uses Eigenvector to rank content Clustering Cosmicient In a Facebook network, the users who occupy the central position (have more direct connections to influential friends in the network) are better positioned to control the flow of social media content. B) Which network map has a higher network density (the one on the left, or the one on the right)? Figure 4: Korean vs. US religious network C) Based on the information in the course pack, chapter 14, what do you think the network coefficient means in context with the diagram above