Social Networking Assignment
The purpose of this exercise is to learn how to use UCINET to calculate and interpret actor centrality scores.
Zachary Karate network: In 1977, anthropologist Wayne Zachary published a study of a karate club that he had observed for three years. From the start he saw a conflict over lesson fees between the club President, John A., and the part-time karate instructor, Mr. Hi. After "a series of increasingly sharp factional confrontations over the price of lessons, the officers, led by John A., fired Mr. Hi for attempting to raise lesson prices unilaterally." Supporters of Mr. Hi resigned and formed a new organization headed by him, while the officers formed a second new club.
Zachary created a symmetrical binary matrix of ties among 34 club members, in which "1" represents a dyadic friendship that he observed outside club classes and meetings. In his analysis, he argued that not all persons were solidly members of the two factions: "Some vacillated between the two ideological positions, and others were simply satisfied not to take sides." Would a reanalysis of Zachary's data by support his interpretation?
ZacharyNet is an undirected binary friendship network whose members are labeled by codes 1 to 34. Person #1 is the instructor, Mr. Hi, and person #34 is the club president, John A.
ZacharyAttr is an attribute file. The first attribute, Strength, is Zachary's codes for how strongly each club member was affiliated with one of two factions:
1 = Hi Strong
2 = Hi Weak
3 = John Strong
4 = John Weak
5 = No affiliation
The second attribute, Newclub, is coded 1 if a member joined Mr. Hi's new club and coded 2 if a member joined the officers' new club.
1. Use UCINET centrality programs to find the degree, closeness, betweenness, and 2- step reach centrality scores for the 34 club members in the ZacharyNet network. Save the outputs for your report.
2. Use UCINET's Excel Matrix Editor to open the ZacharyAttr file and type in a third attribute (Between), the betweenness scores of each actor that you found in step #1. Be careful to enter the correct score for each person. Save this updated file as ZacharyAttr2.
3. In UCINET's Match Multiple Datasets, treat ZacharyNet as the primary file and ZacharyAttr2 as the secondary file. You could name the output files ZacharyNet- Matched and ZacharyAttr2-Matched.
4. In NetDraw, open the two matched files and create a graph of the friendship network. Because ties are not directed, turn off the arrowheads. You may need to move a few points slightly so some lines or labels don't squash together. Save this unmodified diagram as a "jpg" file or use a screen capture for your report.
5. Using NetDraw's Properties menus, make three types of changes: (1) Change the node colors to represent the Strength of each member's affiliation with the factions. (Suggestion: Use two shades of one color, such as pink and red, for the weak and strong affiliates of one faction; and two shades of another color for the second faction. Use black for the two unaffiliated members.) (2) Change the shapes of the nodes to show which Newclub each person joined after the breakup. (3) Change the sizes of the nodes to reflect every member's Between score. Save the modified diagram as a "jpg" file or use a screen capture for your report.
Write a brief report (including diagrams, with single-spaced text) describing the main findings of your analyses; include the following:
Display a table showing the four centrality scores for every actor from Step #1. (You may cut-and-paste from UCINET output, but use Courier font to keep columns aligned!) Identify the most-central actors according to the different centrality concepts and measures. In particular, where do club president John A. #34, and the instructor Mr. Hi #1 rank across the four measures? Are other members very central on some measures, but less-central on others?
Display the two Zachary karate club network diagrams, before and after modifications. Describe what you observe. In particular, comment on the locations of the two faction leaders (Mr. Hi #1and John A. #34) and their friendship ties to other members. To what extent is the graph similar to or different from Zachary's account of the club's social structure? Specifically, do the network locations of the members help to explain which people subsequently joined which new club?
What are your thoughts about the usefulness of the different centrality scores as theoretical concepts and their empirical measures for gaining insights into the internal structures of a network?
Attachment:- Assignment.rar