In the last week ,We learned a lot of new ideas in social media analysis.For me ,the use of graphs in SNA and Betweenness Centrality impressed me the most.Graphs are mathematical structures used to represent relationships between objects.In this way, we can view social network as graphs when doing social media analysis;Betweenness is a centrality measure based on shortest paths which is usually used in complex social network analysis.
To begin with ,I would like to talk about graphs in social network.A social network is always represented as a sociogram,in which nodes represent users and edges represent the relationship between them. A sociogram is realizes by a graph as usual.Graphs offer us a way to describe and capture users’ behavior and interests in terms of their activities.In social network,there are different kinds of graphs,and a discussion graph is a hyper-graph representation of a set of relationships and their associated contexts, extracted from a social media corpus.A key advantage of using discussion graphs is that we can represent and analyse complex relationships.
Then ,I would like to say something about betweennness centrality.When doing social media analysis, one of the fundamental thing is to determine importance(centrality) in a particular vertex(or an edge).Some of the well-known methods are closeness,stress,and betweenness.Of these methods,betweenness is widely used in social analysis. Betweenness Centrality of a vertex is defined by the number of shortest paths in the network that pass through it.Consider a graph G(V,E),where V is the set of vertices representing actors or nodes in the complex network,and E ,the set of edges representing the relationships between the vertices.Teh number of vertices and edges are denoted by n and m respectively .The graphs can be directed or undirected.We assume that each edge has a positive weight W(e).For unweighted graphs,we use W(e)=1.A path from vertex s to t is defined as a sequence of edges.The length of a path is the sum of the weights of edges.Using Betweenness Centrality ,we can get to know the importance of each users in the network.
From your blog, I know that you listened clearly about what the teacher said.You have a good understand about the important of graph in social media.I have some problem in the class,but with the help of your blog,I can solve the problem.
回复删除I found that Xiaoxiao also wrote something in this aspect. Your figure is very philosophical. Where do you find such pictures? Since I read your blogs, I noticed that it's a long way for me to learn social media. Thank you all!
回复删除Having reading your blog, I get so much knowledge about SNA. I learn that you are good at mathematics. And it is a good measure to deal with social media analysis.
回复删除Very nice summary of the main concepts and their detailed description about SNA. I got deeper comprehension after reading this blog, thanks!
回复删除Hi, Gao. After reading your blog, I noticed that you really have a good command of SNA, and I expect to have further discuss with you on the weekend.
回复删除You article makes a brief summary of some course lectures, some part even have more details than the lecture. It helps me review the course content very well. Thanks for sharing.
回复删除Thanks for sharing your thoughts, Wenhan. The use of graphs in SNA and Betweenness Centrality also impressed me the most. We can view social network as graphs when doing social media analysis with that graphs---one of mathematical structures used to represent relationships between objects. When doing social media analysis, one of the fundamental thing betweenness centrality do is to determine importance(centrality) in a particular vertex(or an edge).
回复删除Betweenness Centrality is good way to figure out the important point. And graph is a efficient way to show your result. I learn a lot from your blog. Your explaining about graph is useful to me. And your also help me review the course content. Thank you.
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