Social network analysis (SNA) & applications

Social media tools such as email, discussion forums, blogs, micro-blogs, and wikis are used by billions of people worldwide. As they communicate through these media via desktop and web-based applications on fixed and mobile devices the result is the creation of multiple complex social network structures. The lively interaction and networks of relationships created through these technologies is of growing importance to individuals, organizations, and communities. Understanding how these social media networks grow, change, fail, or succeed is a growing concern to researchers and professionals. The field of social network analysis provides a set of concepts and metrics to systematically study these dynamic processes. The methods of information visualization have also become valuable in helping users to discover patterns, trends, clusters, and outliers, even in complex social networks.

These days, in our class, we learned social network analysis (SNA), the useful network analyzing method. It is the study of the pattern of interaction between actors. In SNA, every activator is present as a node (vertex) and the action between each other is shown by lines (edges) connected to nodes. With these vertices and edges, we can generate some social graph from which we can clearly find the relationship of everyone there.

To analyze a network, several software could be applied, such as UCINET, Pajek, NetMiner, Multinet, Stocnet, Strucuture, NodeXL, ect.

This is one of social grams I made using software NodeXL. The data is collected by Oct 29, and it just shows people in our class.

Social graph can be classified to undirected graph and directed graph. Undirected graph just displays the connecting condition and directed graph can show the direction of each information flow.

Some important indexes could be obtained from SNA.

Degree( degree centrality)-----analyzing in undirected graph. It’s a count of the number of edges that are connected to it. If the edges represented strong friendship ties of individuals in a class, we might say that XX is the most popular person. In directed graph, we analyze in-degree and out-degree, which respectively show the number of edges that point toward the vertex of interest or the vertex of interest points towards.

The following graph is a sub graph of Su Jing, who is the one with the biggest degree(the most popular one) by Oct 29. Generating subgragh image is a useful way to understand complex networks is to view individual sections of the larger graph. It represents the information exchanging condition on a certain individual in the organization.

If we say degree is about popularity, then betweenness centrality is about if the vertex is important in connecting the whole system. Vertices that are included in many of the shortest path between other vertices have a higher Betweenness Centrality than those that are not included.

Closeness centrality presents how close each person is to others in the network. It’s a measure of the average shortest distance from each vertex to each other. A lower closeness centrality score indicates a more central position in the network.

The parameters above are all important when dealing with individuals in the network. If we put the focus on the whole system, we should discuss the density and clustering coefficient…

Nowadays, SNA is widely used in fields such as business link, emergency service, academic collaboration, ect. The methods of information visualization have also become valuable in helping users to discover patterns, trends, clusters, and outliers, even in complex social networks.

Group & individual epistemic cognition

In this blog, I would answer questions left in the last lecture.

1.     Re-answer questions in Class Activity One and Two.

Questions: a) What’s the definition of Social Cloud?  b) what are the possible applications of a Social Cloud ?

l  Activity One

a)     A Social Cloud is a resource and service sharing framework utilizing relationships established between members of a social network.

b)    A Social Computation Cloud; A Social Storage Cloud; A Social Collaborative Cloud; A Social Cloud for Public Science; An Enterprise Social Cloud.

l  Activity Two

a)     A Social Cloud is a resource and service sharing framework utilizing relationships established between members of a social network. A Social Cloud leverages pre-existing trust relationships between users to enable mutually beneficial sharing within the context of a social network.

b)    A Social Computation Cloud: It is widely recognized that extensive computing power remains untapped through personal computers; A Social Storage Cloud: Storage is perhaps the simplest and most standardized resource for everyday users to share and utilize in a Social Cloud; A Social Collaborative Cloud: increasingly collaborations are turning to social networking concepts to share information and resources within diverse user communities, for example MyExperiment.org and nanoHub; A Social Cloud for Public Science: The Social Cloud is an ideal basis on which to create the next iteration of volunteer computing – primarily for solving scientific problems of community interest; An Enterprise Social Cloud: a Social Cloud may be configured differently, depending on the community it serves.

2.     What was the epistemic aim in these 2 activities? Is there any change in epistemic aim? If so, why did you change your mind?

As we can see, the answer in Activity One(individual work) is briefer, and it composed of some short sentence or key words. However, the answer in Activity Two( group work) is more completed and includes more information. In term of epistemic aim, in fact, I just pursue a satisfied answer ‘for the teacher’, cause the time is limited and I’m not interested enough about that article. But in Activity Two, the epistemic aim really changes, we feel free when giving answers, and we pursue more knowledge from group discussion.

3.     Is there any difference in terms of individual and group epistemic cognition, how?

I believe there must be some difference between individual and group epistemic cognition. When people learn things by themselves, if they are not positive learners, or we just say, they are not eager for what they are learning, they may just memorize information as completing a task. It’s inefficient. Opposed to individual learning, group learning can obtain better effect. In a group, we can get information from various aspects, people share their own knowledge and feelings. In a word, I hold the idea that individual learning is static, and group learning is dynamic.

4.     How did you approach to the problem individually and in group, respectively? Is there any difference in the processes involved?

When solving a problem individually, I would get help from related books or the Internet. It’s dull and waste more time as you may totally misunderstand the problem. However, when I am in a group, I would firstly handle the problem by myself, if there’s anything confusing me, I would inquire to other group members. Though this way, I always feel supportive and informed.

In my opinion, the attitude towards individual & group epistemic cognition varies from people to people. Additionally, male and female behave different in these 2 conditions. Generally, females are more likely to work in a group cause they may have a better communicating ability and more sensitive, while males tend to enjoy work alone. In fact, many factors can affect humans’ view on group & individual epistemic cognition. Further work can be done on these fields.