The Objective of This Homework Is to Visualize Your Personal Network Using a Program Called
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Homework 5
The objective of this homework is to visualize your personal network using a program called Visone, and to create a clustered (reduced) graph using the same program. Visone is a free Java-based program available at http://visone.info/html/download.html. Download the Current Version by clicking on visone 2.6.5. This will download a file called visone 2.6.5.jar. Cut this and paste it into a folder – I created one called Visone. Note that this website also has links to a manual, forum and demo.
In addition to downloading visone you will need to download another Java file called EgoNet2GraphML located here: http://visone.info/wiki/index.php/Personal_networks_%28tutorial%29. The purpose of this program is to convert your Egonet interview (your_name.int) into a graphml file that vizone can read. Once you have downloaded this save it in the same folder where you put the visone 2.6.5.jar file. Now you are ready to create your networks in visone. Follow these directions:
1. Double-click the file called EgoNet2GraphML
2. Select File->Open Study and navigate to the folder with the file called Class 2012 Egonet Study and select that study
3. Select File->Open Networks, navigate to the Interviews folder and select your .int file
4. Select File->Export Networks
5. Return to the Visone folder and Double-click the file Visone 2.6.5.jar
6. Select File->Open and navigate to the Interviews folder with your interview
7. Select your interview (You should see one big dot with the number 50 in the middle)
8. In the upper right of the screen click the icon with three connected dots (hovering over it will say quick layout). Now you will see a large completely connected graph. You will have to tell visone you only want to visualize some of the ties.
9. In the pane on the left click on the tab called ‘Selection’
10. In the drop down box by the word ‘attribute’ select the variable Tie
11. Click on the category ‘Not at all likely’
12. From the top menus select Links->Delete Links
13. Click on the category ‘Maybe’
14. From the top menus select Links->Delete Links
15. Click on the quick layout icon at the upper right
16. You should now see a visualization of your network 17. Select File->Export and save this as an image (.jpg or .png) and send this to me
18. Return to the program EgoNet2GraphML
19. Select File->Export clustered networks
20. Under ‘Input Number of Classes’ put the number ‘8’ (there will actually be nine classes, but one will be the default class)
21. Under ‘Assign Class Labels’ type ‘Gainesville’ (this will be class 0) and click OK
22. In the next eight dialog boxes type ‘Florida Not Gainesville’ then ‘US Not Florida’ then ‘North America Not US’ then ‘Latin America’ then ‘Europe’ then ‘Africa’ then ‘Asia’ then ‘Oceania’
23. Now you must define each class
24. Under ‘Attributes Defining Class’ select ‘AlLive’
25. Under ‘Specify attribute values’ select ‘Gainesville’
26. Repeat for each class selecting the appropriate value. NOTE that you may not have alters in some of these so you may not need to define all the classes.
27. Select ‘All Done’
28. Select Export
29. Return to Visone
30. Select File->Open and click on ‘your name clustered.graphml’
31. You should see a large dot with the number 9
32. Select ‘quick layout’
33. Select the tab ‘visualization’
34. Select the drop down menu by the word ‘category’ and select ‘mapping’
35. Select the drop down menu by the word ‘type’ and select ‘label’
36. Click on ‘visualize’ in the lower left
37. Select the drop down menu by the word ‘type’ and select ‘size’
38. Select the drop down menu by the word ‘attribute’ and select ‘class size’
39. Click on ‘visualize’ in the lower left
40. Select the drop down menu by the word ‘type’ and select ‘color’ 41. Select the drop down menu by the word ‘attribute’ and select ‘intra-class tie weight’
42. Click on ‘visualize’ in the lower left
43. Select the drop down menu by the word ‘maximum’ and select the color black
44. Select the drop down menu by the word ‘minimum’ and select the color white
45. Click on ‘visualize’ in the lower left
46. Select the drop down menu by the word ‘type’ and select ‘size’
47. Select the drop down menu by the word ‘property’ and select ‘link width’
48. Select the drop down menu by the word ‘attribute’ and select ‘inter-class tie weight’
49. Click on ‘visualize’ in the lower left
50. You should now see a visualization of your clustered (reduced) network
51. Select File->Export and save this as an image (.jpg or .png) and send this to me