Tag Archives: Blogosphere

Politics 2.0 Conference: Social Network Analysis

“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.

Patrick Philippe Meier

Mapping the Persian Blogosphere (Updated)

Harvard’s Berkman Center has just released a fascinating study on the politics and culture of the Persian Blogosphere.

Berkman’s social network analysis reveals four major network clusters (with identifiable sub-clusters) in the Iranian blogosphere. The authors have labeled the four clusters as 1) Secular / Reformist, 2) Conservative / Religious, 3) Persian Poetry and Literature, and 4) Mixed Networks.

Surprisingly, a minority of bloggers in the secular/reformist pole appear to blog anonymously, even in the more politically-oriented part of it; instead, it is more common for bloggers in the religious/conservative pole to blog anonymously.

Blocking of blogs by the government is less pervasive than we had assumed. Most of the blogosphere network is visible inside Iran, although the most frequently blocked blogs are clearly those in the secular/reformist pole. Given the repressive media environment in Iran today, blogs may represent the most open public communications platform for political discourse. The peer-to-peer architecture of the blogosphere is more resistant to capture or control by the state than the older, hub and spoke architecture of the mass media model.

So are we likely to witness iRevolutions in Iran?

In authoritarian regimes, networked communications can allow participants to get around state control. As an example, Radio B92 in Serbia simply broadcast through the Internet after the government attempted to shut it down. In Iran, satellite TV, Internet based radio stations, cell phones, and other Internet based tools are difficult if not impossible for the regime to control. Costs are generally high for regimes that limit access and connectivity. The Internet will not lead automatically to liberal, open public spheres in authoritarian regimes, but it will make it harder to control and more costly for authoritarian states to do so. […]

Early conventional wisdom held that bloggers were all young democrats critical of the regime, but we found conversations including politics, human rights, poetry, religion, and pop culture. Given the repressive media environment and high profile arrests and harassment of bloggers, one might not expect to find much political contestation taking place in the Iranian blogosphere. And yet oppositional discourse is robust. […]

In conclusion, the authors essentially pose the same question that I am exploring for my dissertation:

The question at hand is not whether the Iranian blogosphere provides a Samizdat to the regime’s Politburo, but whether the new infrastructure of the social nervous system, which is changing politics in the US and around the world, will also change politics in Iran, and perhaps move its hybrid authoritarian/democratic system in a direction that is more liberal in the sense of modes of public discourse, if not necessarily in a direction that is more liberal in the sense of political ideology.

Berkman’s next step should be to move from static network analysis to dynamic analysis. The topology of the network itself over time should reveal other interesting insights. I would recommend they look up Mark Newman at the Santa Fe Institute. Another software program for networks analysis that I would suggest they use is one used to model foodweb dynamics in 3D. This clip demonstrates the program’s features.

Update: I just met with Josh Goldstein, a researcher at the Berkman Center who contributed to this study. Josh was interested in getting more of my thoughts on possible next steps regarding future research using social network analysis (SNA). I suggested they track network parameters (such as degree centrality) over time and find explanations for changes over time. In other words, plot the number of edges that each node (blogger) is connected to over time. For example, how does degree centrality change within the different clusters identified by Berkman after a terrorist events, i.e, events exogenous to the network? Recent research suggests that blogs display a power law relationship between frequency and magnitude, i.e., there are many nodes with few edges, and few nodes with many edges. Does the Persian blogosphere follow this distribution? Why or why not? Does the slope of the power law distribution become flatter or steeper following crises events? Again, why or why not? What social science explanations account for changes in network topologies over time?

Patrick Philippe Meier