“The Politics of Blogging” is the first panel I am bloggling live from at the Politics 2.0 conference in London. In what reflects an increasing interest in applying social network analysis (SNA) to blogosphere dynamics, two of the three papers applied SNA to political blogs in South Korea and Greece. See my previous blog on mapping the persion blogosphere here.
The first presentation was entitled “Social Network Analysis of Ideological Landscapes from the Political Blogosphere: The Case of South Korea.” The presenter argued that South Korea provides an ideal case study for network analysis. The country has seen important grassroots activities prior to the arrival of the Internet; there have been periods of demonstrations, student and worker revolutions/protests. South Korea also has the highest proportion of broadband users in the world. The analysis drew on the 115 blogs of the country’s 219 assembly members and their blog rolls.
The result of the analysis presented an interesting contrast to the results of SNA studies carried out on Republicans and Democrats in the US. South Korea’s political blogosphere was far less polarized. In fact, a substantial number of blogs linked to both the political-right and center parties. The main drawback of the study is the lack of statistical analysis applied to the network map, let alone any statistical analysis of dynamics and trends over time.
The presentation on the Greek political blogosphere applied standard SNA metrics to teethe out some of the underlying structures of the network. The case study focused specifically on the recent debate that took place on the Web with respect to the presidential elections for the Pan-Hellenic Socialist Movement (PASOK).
What I appreciate about this paper is the application of statistical analysis to the network map. Indeed,one reason for using mathematical and graphical techniques in social network analysis is to represent the descriptions of networks compactly and systematically. A related reason for using formal methods for representing social networks is that mathematical representations allow us to use software programs to analyze the network data. The third, and final reason for using mathematics and graphs for representing social network data is that the techniques of graphing and the rules of mathematics themselves suggest properties that we might look for in our networked data—features that might not have occurred to us if we presented our data using descriptions in words. These reasons are articulated by Hanneman and Riddle here.
Another reason I liked the paper is that the authors tied their analysis to the existing literature, e.g., Drezner and Farrel’s paper on the power and politics of blogs. Disclaimer: Professor Daniel Drezner is the chair of my dissertation committee. One of the interesting points that came out of the Q & A was the suggestion of studying negative links, i.e., those bloggers who tell others not to look at certain blogs. I had the last comment of the Q & A session in which I relayed to the panelists Berkman’s recent study on the Iranian blogosphere. My recommendations to the panelists were the same I gave to a colleague of mine at Berkman. These are included in my previous blog on Berkman’s work.
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