1. Influence-Based Community Detection
Lecture 6-4
Influence-Based Community Detection
Ding-Zhu Du
University of Texas at Dallas
First, I want to thank you for you presence. ********In this presentation I will try to introduce The social network which is a theoretical structure to study relationships between individuals, groups, organizations, or even entire societies. 
It is related to a wide range of disciplines. These disciplines include, but are not limited to information science, biology, economics, geography, communication studies, and so on..
The study of social networks begins with the late eighteenth century, two sociologists (Émile [ei'mi:l] Durkheim and Ferdinand ['fɝdənænd] Fer迪南de Tönnies) foreshadowed the idea of social networks in their theories and research of social groups.
Nowadays, we study social networks using network analysis to identify social communities, pick influential person, and design good software.

2. Model-Based Detection
Community Detection
Accurate or not?
Formulation (Model)
Solve formulated problem

3. Influence-based Model

4. Idea People in a same community share common interests in
- clothes, music, beliefs,
movies, food, etc.
Influence each other strongly.
People in a same community share common interests in the same brand of clothes, same kind of music, movies, food, etc.
They influence each other strongly. Therefore, within three steps, the influence is strong.
When companies focus first on meeting the needs of the people they serve, they don’t have to spend big money to attract new customers. And when they stay close to their communities they don’t need market research to tell them what people want.
innovation

5. Definition

6. 5 2 3 4 1

7. 5 2 3 4 1

8. Model

9. Lemma 1
Proof

11. <

12. Lemma 2

13. Proof
basis

14. induction

15. Induction (continue)

16. Induction (continue)

17. Theorem 1

20. Theorem 2
Proof is given later.

21. General Theory

22. Theorem

23. Example 1: A Connection-based Model

24. Lemma
Proof

25. Theorem 1
Theorem 2

26. Example 2: Global Influence
“influence in large part is the ability to reach a crucial man through the right channels, and the more the channels in reserve the better.“
--- Pool and Kochen (1978)

27. Global Influence
Global Influence allows paths with cycles!!

28. Analogy of Connection-based and Influence-based Models
Edge weight w(I,j) is the probability of node j receiving influence from node i.

29. Influence-based Modularity

30. References

31. THANK YOU!