1. Email Alias Detection Using Social Network Analysis Ralf Holzer, Bradley Malin, Latanya Sweeney LinkKDD 2005 Advisor: Dr. Koh Jia-Ling Reporter: Che-Wei, Liang Date: 2008/08/14 1

2. Outline Introduction Alias Detection Method – Data Representation – Ranking Algorithms Experiment 2

3. Introduction Individuals use aliases for various communication purposes Alias detection – Useful to both legitimate and illegitimate applications – Important to understand the extent to which the process can be automated 3

4. Introduction Aliases are listed on the same webpage can indicate there exists some form of relationship between them Many people use several email addresses – This paper attempt to determine which email addresses correspond to the same entity 4

5. Introduction Email addresses, a type of alias, can be distilled from a large number of web pages – Such as class rosters, research papers, discussion boards Email addresses provide a unique mapping from address to a specific entity 5

6. Data Representation Let S represent the set of sources Modeled as an undirected graph G = (I, E) – I be the set of unique email addresses – C ab = |e ab | denote the number of sources associated with each edge connecting a and b 6

7. Ranking Algorithms Ranking method – Top-k list of possible aliases – Shortest path algorithm Used geodesic distance to generate a ranking of nodes closest to a given originating node Relationship strength is augmented with – Number of aliases on a source – Number of collocations of aliases 7

8. Ranking Algorithms Geodesic distance – Length of the shortest path from a to b – Potential aliases are ranked from lowest to highest geodesic distance Multiple Collocation – Two aliases which collocate on more than one webpage signifies a stronger relationship 8

9. Ranking Algorithms Source Size – Strength between two aliases in inversely correlated with the number of aliases in a source Combined – Integrates both of previous assumptions 9

10. Experiment Derived from CMU web pages – 1978 distinct email aliases Data Set Statistics 10

11. Experiment 11

12. Experiment Geodesic Alias Distances 12

13. Experiment 13

14. Experiment 14

15. Experiment 15