Last Blog for IEMS5720

We come to the last Blog for our course. In the last few lectures, two SNA examples are introduced: PageRank and HITS. PageRank is used by Google Internet search engine to assigns a numerical weighting to each element of a hyperlinked set of documents. This help to measure the importance of a particular page.

A new idea – Semantic Web is also introduced. Semantic Web promotes common formats for data on the World Wide Web. The Semantic Web aims at converting the current web of unstructured documents into a "web of data

In final lecture, it talks about Online Social Networks and its Security and Privacy Issues. There are three main security objectives in Online Social Networks. They are

1. Privacy - protection of personal information, message in social network
2. Integrity - the protection of data from being altered by unauthorized parties
3. Availability - availability of user profiles is consequently required as a basic feature, even though considering recreational use

Beside these three aspects, I think Authentication is another important issue in Security Issues of Online Social Networks. In Online Social Networks, we often receive comment or request outside our social network. For example, we receive a friend request in Facebook and he is a friend of my friend, but I didn’t meet him before. How can I authenticate him? Can I trust his profile? 

Let’s consider below situation. I have a friend called Peter. One day, a person called Peter sent me a friend request in Facebook and his profile picture is Peter’s photo. I may accept his request immediately with out further authentication. I think most of the people do the same way liked me. However, this can be very dangerous. I didn’t authenticate his identity and this may expose my personal information to him.

As Online Social Networks become more and more important in our life, we are putting more and more information into the social network. Our personal information becomes easier to be exposed into the social network. Security and Privacy Issues become a very important issues in Social network because the social network is growing too fast.

Social network analysis (SNA)

Social network analysis (SNA)

Social network analysis is the mapping and measuring of relationships and flows between people and community. Each participant in the community is called an actor and depicted as a node.  The nodes in the network are the people and groups while the links show relationships or flows between the nodes. Social network can be represented in graphical representation – Sociogram. This network effectively shows the distinction between the three most popular individual centrality measures: Degree Centrality, Betweenness Centrality, and Closeness Centrality.


SNA Measurements



 
Above social network can be represented in a matrix:

	Alice	Bob	Carol	David	Eva
Alice	-	1	1	1	0
Bob	1	-	0	1	0
Carol	1	0	-	1	0
David	1	1	1	-	1
Eva	0	0	0	1	-

Density

The density is used to measure the closeness of a network, is an indicator for the general level of connectedness of the graph.
Density = (L/ [g(g-1) / 2]) = 2* 6/20  = 0.6


Degree Centrality

Degree centrality of a node refers to the number of edges attached to the node.

	Alice	Bob	Carol	David	Eva
Degree centrality	3	2	2	4	1

Degree centrality can be normalized as below:

	Alice	Bob	Carol	David	Eva
Normalized	0.75	0.5	0.5	1	0.25

Closeness Centrality

An actor is considered important if he/she is relatively close to all other actors. Closeness represents the mean of the geodesic distances between some particular node and all other nodes connected with in

	Alice	Bob	Carol	David	Eva
Closeness centrality	0.2	0.17	0.17	0.25	0.14

Closeness centrality can be normalized as below:

	Alice	Bob	Carol	David	Eva
Normalized	0.8	0.67	0.67	1	0.57

We can find that David got the highest Closeness Centrality. He is most influential because he connected to all other nodes within the network.


Betweenness Centrality

Betweenness centrality is a measure of a node's centrality in a network equal to the number of shortest paths from all vertices to all others that pass through that node.

	Alice	Bob	Carol	David	Eva
Closeness centrality	0.5	0	0	3.5	0

Betweenness centrality can be normalized as below:

	Alice	Bob	Carol	David	Eva
Normalized	0.083	0	0	0.58	0

Result

After getting above measures for Social network analysis, we can find that David got the highest value both Degree Centrality, Closeness Centrality and Betweenness Centrality. David is the center within the social network and is the most influential one.

Second Post for Lecture 4-5

After having 2 more lectures, I learn more about Social Network. We have Social Media, Blogoshere and Social multimedia computing.

Social Media

In the world of Web 2.0, people share information on the internet. This facilitates interactions between people in social network. By making use of social media, people become easier to read information and share resource under Web 2.0.

Blogoshere

 People write blog to share information. If blogs are connected together to create a network, the bloggers form an online community. These kind of online community is very useful. Bloggers can share information in the network. Company also can prompt their product or find out potential client in the social network.

Social multimedia computing

Social multimedia computing makes the social network become more interactivity. Interaction-driven social networks become a major research topic of social network.. 

Direct Social Content Creation

 When we talk about Direct Social Content Creation, the most poplar web site is Wikipedia. Most of the people will think about Wikipedia firstly as an example of Direct Social Content Creation. Wikipedia allows users to create any kind of information. All users can write the content, edit and add recourse and relevant links. However, I think Direct Social Content Creation is everywhere in social network, such as Facebook, Blog, etc… 

After I shared some new or links in my Facebook, my friends may share their opinions on the same topic. We are writing some content on the same topic. It just like Direct Social Content Creation in Wikipedia. The difference is we only share the content to my friends inside Facebook instead of public in the internet. We cannot edit the format in Facebook like Wikipedia. However, the idea of creating the same content is the same. 

I wrote about Direct Social Content Creation in this article of my blog. After several people left comment to discuss Direct Social Content Creation on my article, we created an article about Direct Social Content Creation. The format of my article and comment is different from Wikipedia, but the idea is the same.

We can find that Social Network makes use of Direct Social Content Creation. Or we can say that our Social Network is also made up of Direct Social Content Creation.