1. GRAPH ANALYSIS AND VISUALIZATION PART 1

2. History of Graph 1735

3. History of Graph 1858

4. Graph for mapping social hierarchies

5. Visualisasi zaman sekarang (chord diagram)

6. Visualisasi zaman sekarang (sunburst chart)

7. Visualisasi zaman sekarang (Org Chart)

8. Visualization Process

9. Getting the data Techniques for getting data include the following: File download like SNAP dataset, tweetarchivist.org, data.worldbank.org Report data export that is originated from software solutions in form of flat files or spreadsheet Tools such as NodeXL, Google Spreadsheet Cut and paste (web based publication, online news)

10. Clean : Fix the data A real world e-mail data looks like this : Can we “process” the data directly ? ToFromCcDate BenZoe“ ”12/09/2014 BenZoe JonesTim02/02/2014 BenTimTim; Zoe11/09/2014 BenAnn76.3n/a Ben“ ”“ 01/01/2014

11. Clean : Fix the data Data-quality issues to be considered such as : Inconsistent node names  Zoe or Zoe Jones ? Duplicate Links  if there are many links between the same pair of nodes, is it a common things or not ? (compare email dataset and flight dataset) Self Loop  Tim sent email to Ben and Zoe and to himself also. Isolated nodes  look the final row.

12. After getting the data, choose layout

13. Other layouts

14. Essential Visual Attributes (effective for showing additional data attributes or graph statistics)

15. Explore and Explain After getting the data, visually laying out the graph, and attaching data to visual attributes, you may want to explore the network in more detail to gain some insights. Upon first viewing the graph, the viewer may have some basic questions: What am I looking at? Are there some landmarks ? What is this node (or link) ? What is it connected to ?

16. Isolate Neighbors Paths Drag, Move, modify, delete, group and so on Explanation Sequence Annotate Legend Export

17. Zoom and pan Identify Filter

23. Writing out the node and link files

27. Other examples:

31. Visualization is key to understanding graphs Verify data Check algorithm View information in context Build a visual representation Understand relationships Discover information Find patterns Illustrate and communicate data