Comparison of Social Networks by Likhitha Ravi

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

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

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.

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

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.

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

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)

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

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

Popular Social Networking Sites Facebook Twitter LinkedIn MySpace Google Plus+

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

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.

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?

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

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

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.

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 .

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

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

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

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