Presents the work of Mislove et al. (2009) on the characteristics of Online Social Networks. This presentation was given in IANLab meeting, on Mar 29th, 2011 @ SITI.

1. A closer look at Online Social
Networks (OSNs)
Universidade Lusófona, IANLab meeting
Waldir Moreira
15/02/2011
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2. Agenda
 Why study Online Social Networks?
 Objects of Study
 Crawling on OSNs
 Identified Structural Properties
 Summary
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3. Why study Online Social Networks?
 Evaluate current systems (Improvements)
 Design future OSN-based systems
– Role in personal and commercial online interaction
– Location and organization of data and knowledge
 Understand impact of OSNs on Internet
– OSNs are popular and bandwidth-intensive
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4. Why study Online Social Networks?
 Detect trusted/influential users
– Trust on each other (Email Spam)
– Common interests (Improve Internet search)
 Routing ☺
– Increase reliability of used links
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5. Objects of Study
 “Pure” social networking site
– Orkut: finding and connecting users
 For publishing, organizing, and locating content
– Flickr
– YouTube
– LiveJournal
 Most popular social networking sites and allow to
view links out of any user
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6. Crawling OSNs
 Publicly accessible information
 Automated scripts on a cluster of 58 machines
 Breadth-first search (BFS)
– Retrieve the list of not-visited friends for a user
– Add it to the list of users to visit
– Continue until exhaust the list
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7. Identified Structural Properties
 Significant degree of link symmetry even in OSNs
with directed links
– Increases overall connectivity and reduces its
diameter 
– Dilutes importance of reputable sources 
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8. Identified Structural Properties
 Power-law node degrees
– Consistent behavior with a power-law network
– Majority of nodes have small degree, and few
nodes have significantly higher degree 
– Distribution of outgoing links is similar to that of
incoming links
– Active users also tend to be popular
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9. Identified Structural Properties
 Power-law node degrees
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10. Identified Structural Properties
 Path lengths and diameter
– Social networks have significantly shorter average
path lengths 
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11. Identified Structural Properties
 Link degree correlations
– How often nodes of different degrees connect to
each other
– knn, mapping between outdegree and the average
indegree of all nodes connected to nodes of that
outdegree.
– Trend for high-degree nodes to connect to one
another is observed in all networks except YouTube
– Forming a “core” of the network.
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12. Identified Structural Properties
 Link degree correlations
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13. Identified Structural Properties
 Densely connected core
– Necessary for the connectivity of the network
– Strongly connected with a relatively small diameter
– Densely connected core comprising 1% to 10% of
the highest degree nodes 
– May have implications for information flow, for trust
relationships, and for the vulnerability 
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14. Identified Structural Properties
 Tightly clustered fringe
– Highly-clustered local neighborhoods outside core
– Significant clustering among low-degree nodes 
– People tend to be introduced via mutual friends
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15. Identified Structural Properties
 Groups (shared interests)
– Users in a group not necessarily have a link to each
other (SociaCast assumption) 
– User groups represent tightly clustered communities
– Members of smaller user groups tend to be more
clustered than those of larger groups
– Low-degree nodes are part of very few
communities, while high-degree nodes are members
of multiple groups 
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16. Summary
 Validate
– Power-law (degree distribution)
– Small-world (small diameter and high clustering)
– Scale-free (high-degree nodes tend to be connected
to other high-degree nodes)
 Observe a high degree of reciprocity in directed user
links, leading to a strong correlation between user
indegree and outdegree.
 Large, strongly connected core of high-degree
nodes, surrounded by many small clusters of low-
degree nodes.
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17. References
[Mislove et al. 2009] A. Mislove, P. Druschel, M. Marcon, B.
Bhattacharjee, and K. P. Gummadi, "Measurement and Analysis
of Online Social Networks." IMC'07, 2007.
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18. Thanks!
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19. Extra
http://fellows-exp.com/
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