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9thTripleHelix Int’l Conference,[object Object],The structure of ,[object Object],Politicians’ Twitter information flow ,[object Object],                                        : A case of South Korea,[object Object],Ho Young Yoon,[object Object],WCU Webometrics Institute, Yeongnam University, Korea,[object Object],Associate Professor, Dept. of Mass Media & Communication, YeungnamUniversity, Korea,[object Object],Han Woo Park*,[object Object],* corresponding author and presenter,[object Object]
9thTripleHelix Int’l Conference,[object Object],Twitter Network regarding politics,[object Object],What about Twitter network between politicians?,[object Object],√ The relation between the public and politicians ,[object Object],i.e)  ,[object Object],“online soapbox, a way to reach large audience (conservative),[object Object],“more as a way to connect people with each other (progressive),[object Object],√ Individuality based research,[object Object],i.e),[object Object], “one-way interactions rather than two way”,[object Object], “adoption by peer pressure (same committee, same region),[object Object]
9thTripleHelix Int’l Conference,[object Object],Politician Network,[object Object],Hyperlink,[object Object],Indirect Network,[object Object],[object Object],-   set of people ,[object Object],     to connect,[object Object],Embedded Network,[object Object], co-existence of ,[object Object],the public and peers,[object Object],network boundary,[object Object], setting,[object Object],Mediated Network,[object Object],[object Object],    representation,[object Object],[object Object],   of people ,[object Object],  to connect,[object Object],Bill cosponsorship,[object Object],Twitter Network,[object Object]
9thTripleHelix Int’l Conference,[object Object],Politicians, Embedded in Twitter platform,[object Object],Network Boundary,[object Object],Public Representation,[object Object],√ The existence of other politicians in the same media platform,[object Object],->Social Pressure to connect other politicians ,[object Object],Network of social ritual,[object Object],√ The public directly gaze the relationship between politicians,[object Object],->Public Representation of social relation,[object Object],Network of political support,[object Object]
9thTripleHelix Int’l Conference,[object Object],Data,[object Object],√ Nov 2010, API application, 189 Korean Politicians,[object Object],National Assembly Members ,[object Object],and Political Figures (i.e. Mayors or Governors) ,[object Object]
9th TripleHelix: Politicians Twitter network - a case of S. Korea
9thTripleHelix Int’l Conference,[object Object],Politicians, Embedded in Twitter platform,[object Object],Network Boundary,[object Object],Public Representation,[object Object],√ The existence of other politicians in the same media platform,[object Object],->Social Pressure to connect other politicians ,[object Object],->High Density than other media platform,[object Object],->High Reciprocity,[object Object],√ The public directly gaze the relationship between politicians,[object Object],->Public Representation of social relation,[object Object],->The gravity of attraction to popular politicians on Twitter,[object Object],->More public followers, more connections from politicians,[object Object]
9thTripleHelix Int’l Conference,[object Object],Research Result,[object Object],1) Source: Hsu and Park (2011).,[object Object],- Based on members of the 18th National Assembly (isolated nodes excluded).,[object Object]
9thTripleHelix Int’l Conference,[object Object],Research Result,[object Object]
9th TripleHelix: Politicians Twitter network - a case of S. Korea
9th TripleHelix: Politicians Twitter network - a case of S. Korea
9thTripleHelix Int’l Conference,[object Object],Politician Network (Following and Mention Network),[object Object]
9th TripleHelix: Politicians Twitter network - a case of S. Korea
9thTripleHelix Int’l Conference,[object Object],Conclusion,[object Object],Politicians Twitter Following-follower Network,[object Object],Politicians  Twitter Mention Network,[object Object],Network of social ritual,[object Object],Network of political support,[object Object]
9th TripleHelix: Politicians Twitter network - a case of S. Korea

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9th TripleHelix: Politicians Twitter network - a case of S. Korea

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Notas del editor

  1. The research on Twitter has been developing, especially with the relation between Twitter and Politics.I think previous studies could be categorized into two. The relation between public and politiciansIndividual level research focusing on personal behaviors of politiciansHowever, I’ve not seen a study on politician’s Twitter network
  2. However, it is intriguing to see how politicians’ Twitter network can co-opt with previous research on politicians networkRegarding politicians’ network, the most well-known network is probably bill cosponsorship network,Which is indirect network based on bill legislation. In this case, the boundary of politicians to connect is based on set of people to sign rather than whole politicians.And we can also think of hyperlink network between politicians, which is mediated network by politicians’ hompages or blogs.Unlike the cosponsorship, it is direct link to other politicians and also public representation to the public. However, they lack the property that politician’s Twitter network has.First of all, Twitter network is the only network that the public and peer politicians are located in the same platform Therefore, second, the network boundary is totally different from previous two network.
  3. To elaborate, this is a unique feature of Twitter networkSince politicians are embedded in the Twitter,Where, network boundary is fixed, like the existence of other politicians in the same media platform, they have a definite set of people to connect as soon as they enter Twitter space,So there might be a stronger social pressure to connect other politicians…… that leads us to see that twitter network can be a network of social ritual like saying hello to everyone.Another feature is that the co-existence of the public influence relationship between politicians on Twitter because they are within direct gaze of the public, which makes politicians to consider how their connections to be seen by public…. This lead us it could be possible that they want to show political support to popular politicians on Twitter.
  4. So, we want to see politician’s Twitter network really different from previous studies on politicians’ Network and collected data.We have collected 189 politicians and divided them into two political groups or ruling party and oppsition parties because literally there were too many parties in South Korea.
  5. In fact, dividing into two groups seems appropriate because our CONCUR analysis, which is block modelling technique to divide blocks, shows that it really matches with network-based group distinction.
  6. The story goes like this.Since Politicians Twitter network has relatively fixed network boundary so that it gives more social pressure to connect other politicians, meaning the Twitter network will show higher network density than other types of media network (such as hyperlink network of blogs or homepages) and more reciprocity, which is bill cosponsoring network has revealed that the most important principle to connect.In addition, because of the public, politicians concerns how their connections to be seen so that they may connects politicians who are popular on Twitter, managing their impression and relation with other politicians.
  7. Our result seems quite relevant to these stories. This is network density table.. (explanation…)
  8. And this is cohesiveness of network table.. ( explanation)
  9. Then what makes difference between the following-follower network and mention network?We conducted EGRM model to see the difference.The difference is that, as you see, reciprocity. Check this Reciprocity AAB .. (explanation)
  10. Then, we saw that the following-follower network and mention network have different logics and the following-follower network is based on reciprocity.The question is what makes mention network different from the following-follower. It turns out that, as we put it, the more popular a politicians is on twitter, the more politicians mention to the politicians.(explanation of two variables.. )
  11. It could be more intuitive to see through graphics.We depicted Politicians’ Twitter network. We have drawn the mention network over the following-follower network(explanation, if necessary)
  12. The distribution between politician confirms this The following-follower network shows a linear function, meanwhile the mention network is more similar to power-law distribution.Reciprocity-based connections is, basically, “ I link to people who linked to me” .. So linear functionThe gravity to popular person is that “I mention to people who get most attention” So preferential attachment principle to connect…leads power-law function.
  13. (conclusion)