Comparison of Social Networks
by Likhitha Ravi
Outline
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Problem
Importance of the study
Challenges of the study
Recap
Data Collection
Metrics
Conclusion
Outline
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Problem
Importance of the study
Challenges of the study
Recap
Data Collection
Metrics
Conclusion
Problem
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No studies on Google plus network?
We compares the social networks in the field of complex networks?
- Not many
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What features are affected by the directed network and undirected
network versions?
- Some of the impressive features are shortest paths,
reciprocity and resilience.
Outline
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Problem
Importance of the study
Challenges of the study
Recap
Data Collection
Metrics
Conclusion
Importance of the study
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This study helps the marketing companies in choosing a network
which has high rate of information spread.
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This study gives basic information of the Google plus metrics to the
potential researchers.
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It also predicts the advantages and disadvantages of a network
based on its structure.
-Some default predictions of an undirected and directed networks.
Outline
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Problem
Importance of the study
Challenges of the study
Recap
Data Collection
Metrics
Conclusion
Challenges of the study
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Data Collection
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Directed Network (Done)
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Undirected Network (? Facebook network or Converting the directed
network to undirected)
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Visualization Tool
(Still exploring the right tool )
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Analysis
(the metrics code provided by Dr.Gunes)
Outline
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Problem
Importance of the study
Challenges of the study
Recap
Data Collection
Metrics
Conclusion
What is social network?
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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
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Facebook
Twitter
LinkedIn
MySpace
Google Plus+
Important elements in OSN
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Actors
Indegree
Outdegree
Hubs
Bridges
Shortest path
Reciprocity
Clustering coefficient
Power law
Resilience
Summary of findings from past studies of Social
Networks
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the intensity of message posting involving two users does not depend
clearly on their degree similarity or difference.
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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.
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Undirected networks are more resilient to the changes in the network
compared to the directed networks.
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Social network analysis can also be used in solving problems in task
oriented networks and online market places.
Missing in previous studies
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Google Plus being a new social network, it gives researchers an
opportunity to study, understand, analyze its features.
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For a directed network
-indegree, out degree, reciprocity
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How resilient is it compared to the undirected networks like
facebook?
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What is the clustering coefficient?
What are the hubs, authorities?
Is power law observed?
Outline
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Problem
Importance of the study
Challenges of the study
Recap
Data Collection
Metrics
Conclusion
Data Collection
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Technologies used
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Python script
-NetworkX
- add_Edge()
- node()
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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
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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
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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
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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
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Resilience
- Randomly remove two central nodes from network (tool)
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Reciprocity
-Directed (formula)
-Undirected ()
Outline
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Problem
Importance of the study
Challenges of the study
Recap
Data Collection
Metrics
Conclusion
Conclusion
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The study and the methods are used to
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compare the network metrics
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Find the underlying advantages and disadvantages
Data Collection
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Directed network –Google plus data
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Undirected network –(?)
Data Analysis Results (To do)
- Compute the metrics and compare