1. Comparison of Social Networks by Likhitha Ravi

2. Outline Problem Importance of the study Challenges of the study Recap
Data Collection
Metrics
Conclusion
I will discusses the problem, importance, challenges, recap, m anc

3. Outline Problem Importance of the study Challenges of the study Recap
Data Collection
Metrics
Conclusion

4. Problem No studies on Google plus network?
We compares the social networks in the field of complex networks?
- Not many
What features are affected by the directed network and undirected network versions?
- Some of the impressive features are shortest paths, reciprocity and resilience.

5. Outline Problem Importance of the study Challenges of the study Recap
Data Collection
Metrics
Conclusion

6. Importance of the study
This study helps the marketing companies in choosing a network which has high rate of information spread.
This study gives basic information of the Google plus metrics to the potential researchers.
It also predicts the advantages and disadvantages of a network based on its structure.
-Some default predictions of an undirected and directed networks.

7. Outline Problem Importance of the study Challenges of the study Recap
Data Collection
Metrics
Conclusion

8. Challenges of the study
Data Collection
Directed Network (Done)
Undirected Network (? Facebook network or Converting the directed network to undirected)
Visualization Tool
(Still exploring the right tool )
Analysis
(the metrics code provided by Dr.Gunes)

9. Outline Problem Importance of the study Challenges of the study Recap
Data Collection
Metrics
Conclusion

10. What is social network? -Wikipedia
A social network is a social structure made up of individuals (or organizations) called "nodes", which are tied (connected) by one or more specific types of interdependency, such as friendship, kinship, common interest, financial exchange, dislike, sexual relationships, or relationships of beliefs, knowledge or prestige.
-Wikipedia

11. Popular Social Networking Sites
Facebook
Twitter
LinkedIn
MySpace
Google Plus+

12. Important elements in OSN
Actors
Indegree
Outdegree
Hubs
Bridges
Shortest path
Reciprocity
Clustering coefficient
Power law
Resilience

13. Summary of findings from past studies of Social Networks
the intensity of message posting involving two users does not depend clearly on their degree similarity or difference.
It was found that correlation between an user’s popularity and activity is based on the number of messages posted to other walls and received from other users, but not based on how often he or she writes to own wall.
Undirected networks are more resilient to the changes in the network compared to the directed networks.
Social network analysis can also be used in solving problems in task oriented networks and online market places.

14. Missing in previous studies
Google Plus being a new social network, it gives researchers an opportunity to study, understand, analyze its features.
For a directed network
-indegree, out degree, reciprocity
How resilient is it compared to the undirected networks like facebook?
What is the clustering coefficient?
What are the hubs, authorities?
Is power law observed?

15. Outline Problem Importance of the study Challenges of the study Recap
Data Collection
Metrics
Conclusion

16. Data Collection Technologies used -gives 15 results at a time
Python script
-NetworkX 
- add_Edge()
- node()
Google Plus API
-gives 15 results at a time
-it gives the results of only users who have choose to be visible in search results are

17. Google Plus Network Size of the network is 2,68,912.
Actors - Friends of friends and friends of 958 people in Reno.
Edges – If both are friends or if one is following the other.

18. Undirected Network Not sure yet. (Facebook ?)
Planning to convert the Goggle plus network by eliminating redundant nodes and also adding the followers as friends.
Reason- We want to compare the networks with similar structure, size, and interconnections and see how the hubs, authorities, shortest paths change when the network is directed and undirected .

19. Data analysis Clustering Coefficient – metrics code
Density of the network - formula
Information Spread – (betweeness) - metrics code
Reachability – Randomly selecting two nodes
Degree of the Actors – tool
Shortest Paths & longest Paths– tool
Hubs & Authorities - tool

20. Data Analysis Resilience
- Randomly remove two central nodes from network (tool)
Reciprocity
-Directed (formula)
-Undirected ()

21. Outline Problem Importance of the study Challenges of the study Recap
Data Collection
Metrics
Conclusion

22. Conclusion The study and the methods are used to Data Collection
compare the network metrics
Find the underlying advantages and disadvantages
Data Collection
Directed network –Google plus data
Undirected network –(?)
Data Analysis Results (To do)
- Compute the metrics and compare