Those are all about measuring data about a social network. Each index has it own mathematical algorithm to calculate, and some algorithms are similar to each other.Here, I am not going to talk about how the data can be calculated, instead I am going to provide some perspectives from myself about the use of these data.
How can these data serve us?
Firstly, I want to use an example of Weibo to explain my thoughts. In Weibo or many other social networks, people speak out their special thoughts and others can make comments beneath their articals or blogs, and some thoughts may attract a lot of attention and some may not. Weibo has done some assortment according to several measuring index mentioned in the first section.
Yao Cheng,a famous star in China is well known as queen of Weibo for that she has the most fans in this social network.
Have you ever thought that your own idea can be shared by 26603377 other persons? I have never imagine this circumstance until social network appeared. What is more, the quantity of people who can share blogs of this star can be further bigger due to the function of "share this blog to other" function. So, what I want to say is, in this case, Yao Chen may have the highest actor prestige, degree centrality and some other indexes.
For Yao Cheng, those data can help her become more famous and then attract more advertisements. For advertisers, through those data, they can analyze which group of people who like to read Yao Cheng's blogs and decide whether their advertisements can get enough profits in her blogs, which in return can benefit Yao Cheng. For common users like me, I can get the main trend of the society culture or civilization from observing different comments beneath the hot blogs from Yao. Maybe that is why some media critics named Weibo the mirror of the whole society, and why Weibo has been aimed to by dealers in quantity.
This picture shows the comments beneath one of the hottest micro-blog, and we can see two advertisement here which can prove the high density of advertisements in Weibo.
Next, I also want to talk about the social network graph of facebook. If we settle two groups of people who played facebook. One group consists of 50 users who have low log in frequency and barely gave comments, while the other group consists of 50 famous users in facebook. I think the centrality and prestige of second group will be higher than data of group one.
I think her name is "Yao Chen" other than "Yao Cheng"...
回复删除Revenue model is rather a problem for Sina Weibo. I also believe that SNA could help sell its advertisement better.
Revenue model is a big problem. We already have seen lots of ads on weibo, however most of them are posted by common users (or spammers, bots) in which case Sina does not only get no money but also has to put some efforts to do spam filtering.
删除I should be the group which has the lowest centrality and prestige in the Facebook.And I find weibo advertisement not just show in the weibo of some famous people,I can see it anywhere even in my weibo.:(
回复删除The advertisement fee for Yao Chen's weibo probably is the most expensive.
回复删除Clever girl!After reading your blog,I got to know I can have many fans in weibo through the method you mentioned above, just be active！
回复删除For instance of Yao Chen, who is called the queen of Weibo, you give us a clear way to understand some parameters of SNA. What is more, you tell us how to use these data to analyse a user role in social networking structure.
回复删除It seems that Doppler effect also take place in the Social Network. It is very likely that the popular ones get more and more popular while the ones without concern left isolated.
回复删除As you mentioned in the article, I think it is a new way of advertisement since the emergence of Twitter/Weibo. And the stars of SNS can recieve more revenue from the advertisement system of this kind of business model, it also encourages the Social Network stars making more effort to keep its popularity.
As you asked in your blog, How can these data serve us? Sometimes we just focus on the methods to analyze all the data we collected. But we may ignore the application of these results. I think It's a good view to explain the applcations of SNA in daily life.
回复删除quite a good view to explain the application of SNA
回复删除yep, we can easily tell there are some difference in degree , density and etc.
I can't agree more with your article as I also consider the "celebrity effect". I believe if a famous star occur in the social network, not only the user centrality would rise up but also the user group would large up.
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