Summary by Patrick Skevik

Measurement and Analysis of Online Social Networks
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This paper analyses the structure of social networks in four different social sites.

Social networks within these four sites are regarded as links shared between users,
either through a forward link or an undirected link. Forward link means a user can 
link to another user without the second user linking back. The undirected link
means both users must agree to link to each other. 

Crawling these sites were done with either an API or though scrapping HTML if
no such API was available. In the case of Orkut, this caused minor problems as
they had no access to an API and was severly limited in their scrapping abilities, 
leaving them with a minor subset of the users available. They did however account
for this in the paper.

Each social network appears to follow the power-law structure where high-degree nodes
connect more to other high-degree nodes.

Suggested questions:
 * How does potential dead accounts affect a study like this?


Measurement and analysis of online social networks
--- Summary by Ying Li

This paper crawled a large scale of data from four popular online social
networking sites Flickr, LiveJournal, Orkut and YouTube, in order to have a
better understanding on the graph structure of online social networks.

This study does not only give inspiration to future distributed online social
network, but also have impacts on studying off-line social network, utilizing
online campaigning and viral marketing, and etc.

The analysis shows there is the pattern of power-law, small-world, and scale-
free behavior existing in the four social networking sites that are under
investigation. More specifically, there is strong correlation between the
connected users in terms of link degrees.

The findings from the study indicates both the strength and weakness of online
social network, in the sense that the well-connected network can be an
advantage for information spreading but can also be used by spam or viruses.

Suggested questions:
How is the online social network more distinguished from offline social network?

Measurement and analysis of online social networks 
summary by guangyu han
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The paper uses a crawler to crawl through
online social networks such as Youtube, Orkut, Flickr and LifeJournal. The
author collect a data set by crawling cover the following number of users: 1.8
million out of 6.8 million (26.9%) for Flickr, 5.2 million of 5.5 million
(95.4%) for LiveJournal, and 3.0 million out of 27 million (11.3%) for Orkut.
it gives us a tangible view of properties in large social networks

Many of the properties in the paper were already proposed before
Adamic et Al [3]  found small-world behaivor, and local clustering.
Kumar et Al. [26] found a large strongly connected component.

All networks follow a power-law is propotional to K^(-i).
Small-world property. Very short path length
Scale-free means  nodes with high degrees are connected to other nodes with high degrees

questions 
what is the  influence of fake users  when performing the  analysis?
and How to avoid  these influence .

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