Complexity and Social Networks Blog

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26 February 2006

More on NSA network analysis....

More on NSA: A piece in yesterday’s NYT provides more insight in the data analysis capacity of NSA. It confirms that the NSA is likely doing a combination of social network analysis with voice recognition to select out promising snippets for further (human) examination.

Some excerpts:

… databases [are] maintained at an AT&T data center in Kansas, which now contain electronic records of 1.92 trillion telephone calls, going back decades.

A former AT&T official who had detailed knowledge of the call-record database said the Daytona system takes great care to make certain that anyone using the database, whether AT&T employee or law enforcement official with a subpoena—sees only information he or she is authorized to see, and that an audit trail keeps track of all users. Such information is frequently used to build models of suspects’ social networks.
The official… said every telephone call generated a record: number called, time of call, duration of call, billing category, and other details…. [N]ames, addresses, credit card numbers are in a linked database….

The National Security Agency has invested billions in computerized tools for monitoring phone calls around the world—not only logging them, but also determining content—and more recently in trying to design digital vacuum cleaners to sweep up information from the Internet.

An earlier NSA patent, in 1999, focused on a software solution for generating a list of topics from computer-generated text. Such a capacity hints at the ability to extract the content of telephone conversations automatically. That might permit the agency to mine millions of phone conversations and then select a handful for human inspection.

In 2003, Virage [a company]… began supplying a voice transcriptions product that recognized and logged the text of television programming for government and commercial customers. Under perfect conditions, the system could be 95% accurate in capturing spoken text. Such technology has potential applications in monitoring phone conversations as well.

From: “Taking Snooping Further: Government Looks at Ways to Mine Databases,� by John Markoff (B1), NYT, Feb 25.

Posted by David Lazer at 10:17 AM | Comments (0)

24 February 2006

Snowman and snowdog added to the KSG by PNG Team

Some of you might have seen the following news on the frontpage of the Kennedy School of Government website:

We decided to reveal that some of the PNG fellows are behind this sudden appearance as they concluded that snow was just perfect last Wednesday for building a snowman and a snowdog. Unfortunately, most of it melted within 2 days before a new cold front hit MA last weekend.

Posted by Alexander Schellong at 2:00 PM | Comments (0)

21 February 2006

A quick mention of The International Workshop and Conference on Network Science that is coming up in late May. It has a first rate set of folks putting it together (I would note, btw, that a majority of their organizing committee are former presenters in the CCCSN series). There is some support available for doctoral students/postdocs. Here's the blurb on it:

The International Workshop/School and Conference on Network Science will bring together leading researchers and practitioners in network science - analysts, modeling experts, and visualization specialists with graduate students from many different research areas for interdisciplinary communication and collaboration.

The primary objective of the Workshop/School and Conference is to facilitate interactions between social and behavioral scientists and the many other disciplines interested in and utilizing network science.

The event will be held over a two week period at Indiana University, Bloomington, Indiana, during May 2006. The first week, the Workshop/School, will feature tutorials (which present basic, educational material) focusing on a variety of network science research areas. It aims to present and support experimental, theoretical and applied network research by educating the research community on standard network data, tools, and powerful computational resources. The Conference comprises talks by social and behavioral scientists, information scientists, biologists, statistical physicists, mathematicians and statisticians.

Registration deadline: April 21, 2006

Abstract Submission deadline: March 31st, 2006

Posted by David Lazer at 7:58 AM | Comments (0)

20 February 2006

How to measure relations: the coming paradigm shift

The dominant way to measure relations in social network analysis (SNA) is still based on self-report data. I predict that over the next 10-15 years there will be a dramatic shift in how this foundational construct is measured, from self-report to behavioral measures. The reason for this is simply that people leave vastly more traces of their behaviors now than they used to. Nathan's entry of last week offers a remarkable example of this.

We see an opening wedge of studies using observational data—e.g., see Tyler et al. and Diesner and Carley, which used e-mail data. However, if you look at sociology and OB publications (for ex), the vast majority of social network articles still rely on self report data. Further, most of those papers interpret the results as if they reflect actual behavior.

This is potentially troubling, because research suggests that the correlation between self report and behavior is surprisingly low. The classic work in this vein comes in a series of studies co-authored by Bernard Killworth, and sometimes Sailer. (Note that Freeman et al. found that people do better at recalling long term social structure than short term interactions.)

Putting aside the correlation between observational and self-report data, these are distinct constructs, and which one is interested in depends on ones research questions. Clearly, in certain cases behavior is all that matters—if you are interested in the transmission of STD’s, then a key question is how to eliminate the deviation between self reports and actual behavior (e.g., see Brewer et al.). However, those deviations, as Corman and others have explored, are not random. Even in the context of sexual behavior, one would guess that recall is correlated with (for example) emotional significance. This is not so interesting, perhaps, in understanding the spread of sexual diseases, but might be interesting for other research questions.

In any case, I do think that this is an area that requires a great deal more attention over the next few years. In particular, there needs to be more attention to (1) the link between different types of interaction behaviors and self-reported relations, and (2) the interaction between the two (e.g., it may matter if I talk a lot with my friend or not, not just whether they are (a) someone I see as a friend, or (b) someone I talk a lot with).

(Note, btw, that this entry benefited from a recent exchange on the Socnet listserv on “CSS & ‘A Million Little Pieces’�)

The dominant way to measure relations in social network analysis (SNA) is still based on self-report data. I predict that over the next 10-15 years there will be a dramatic shift in how this foundational construct is measured, from self-report to behavioral measures. The reason for this is simply that people leave vastly more traces of their behaviors now than they used to.

We see an opening wedge of studies using observational data—e.g., see Tyler et al. and Diesner and Carley, which used e-mail data. However, if you look at sociology and OB publications (for ex), the vast majority of social network articles still rely on self report data. Further, most of those papers interpret the results as if they reflect actual behavior.

This is potentially troubling, because research suggests that the correlation between self report and behavior is surprisingly low. The classic work in this vein comes in a series of studies co-authored by Bernard Killworth, and sometimes Sailer. (Note that Freeman et al. found that people do better at recalling long term social structure than short term interactions.)

Putting aside the correlation between observational and self-report data, these are distinct constructs, and which one is interested in depends on ones research questions. Clearly, in certain cases behavior is all that matters—if you are interested in the transmission of STD’s, then a key question is how to eliminate the deviation between self reports and actual behavior (e.g., see Brewer et al.). However, those deviations, as Corman and others have explored, are not random. Even in the context of sexual behavior, one would guess that recall is correlated with (for example) emotional significance. This is not so interesting, perhaps, in understanding the spread of sexual diseases, but might be interesting for other research questions.

In any case, I do think that this is an area that requires a great deal more attention over the next few years. In particular, there needs to be more attention to (1) the link between different types of interaction behaviors and self-reported relations, and (2) the interaction between the two (e.g., it may matter if I talk a lot with my friend or not, not just whether they are (a) someone I see as a friend, or (b) someone I talk a lot with).

(Note, btw, that this entry benefited from a recent exchange on the Socnet listserv on “CSS & ‘A Million Little Pieces’�)

References:
Killworth, P. D. and H. R. Bernard. 1976. Informant accuracy in social network data. Human Organization 35:269-286.

Bernard, H. R. and P. D. Killworth. 1979. Informant accuracy in social network data II. Human Communication Research 4:3-18.

Killworth, P. D. and H. R. Bernard. 1979. Informant accuracy in social network data III: A comparison of triadic structures in behavioral and cognitive data. Social Networks 2:19-46.

Bernard, H. R., P. D. Killworth, and L. Sailer. 1980. Informant accuracy in social network research IV: A comparison of clique-level structure in behavioral and cognitive data. Social Networks 2:191-218.

Bernard, H. R., P.D. Killworth and L. Sailer. 1982. Informant accuracy in social-network data V: An experimental attempt to predict actual communication from recall data. Social Science Research 11:30-66.

Joshua R. Tyler, Dennis M. Wilkinson, Bernardo A. Huberman, Email as Spectroscopy: Automated Discovery of Community Structure within Organizations

Jana Diesner, Kathleen Carley, Exploration of Communication Networks from the E-mail Enron Corpus

Linton C. Freeman, A. Kimball Romney, Sue C. Freeman American Anthropologist, New Series, Vol. 89, No. 2 (Jun., 1987) , pp. 310-325

Brewer, D. D., Potterat, J. J., Muth, S. Q., Malone, P. Z., Montoya, P. A., Green, D. A., Rogers, H. L., & Cox, P. A. (2005). Randomized trial of supplementary interviewing techniques to enhance recall of sexual partners in contact interviews. Sexually Transmitted Diseases, 32, 189-193.

Corman, S. R., & Scott, C. R. (1994). Perceived communication relationships, activity foci, and observable communication in collectives. Communication Theory, 4, 171-190.

Corman, S. R., & Bradford, L. B. (1993) Situational effects on the accuracy of self-reported organizational communication behavior. Communication Research, 20, 822-840.

Corman, S. R., & Krizek, R. L. (1993) Accounting resources for organizational communication and individual differences in their use. Management Communication Quarterly, 7, 5-35.

J.C. Johnson and M.K. Orbach (2002) "Perceiving the Political Landscape: Ego Biases in Cognitive Political Networks". Social Networks 24 291-310.

Posted by David Lazer at 5:38 AM | Comments (0)

15 February 2006

Spring schedule for Cambridge Colloquium on Complexity and Social Networks

Here's the Spring 2006 schedule for the Cambridge Colloquium on Complexity and Social Networks:

March 6: Brinton Milward, University of Arizona, "Dark Networks as a
Governance Problem," Bell Hall, Belfer Building, Kennedy School, Harvard.

April 10: James Rauch, UCSD, "Clusters and Bridges in Networks of
Entrepreneurs," 1737 Cambridge Street, Room N401.

April 20: John Casti, Complexica and Santa Fe Institute, “Why the Future
Happens: Socionomics and the Science of Surprise,� (videocast from ETH,
Zurich, with Blake LeBaron of Brandeis as discussant), Swiss Consulate, 420
Broadway, Cambridge.

May 8: Stuart Kauffman, The University of Calgary and Santa Fe Institute,
TBD, 1737 Cambridge Street, Room N401.

All events will be at noon, with a light lunch to be served.

Most events are podcast, and for a handful we will have video, available at
www.ksg.harvard.edu/netgov. All talks are paired with online discussions
through the netgov blog.

Posted by David Lazer at 10:18 PM | Comments (0)

14 February 2006

What would you do with the telephone call network of an entire country?

I’m beginning a collaboration with British Telecom in an effort to analyze their massive call network dataset. This is a dynamic, directed network that contains ~250 million nodes (ie: distinct phone numbers) and ~2000-5000 edges (ie: calls) generated each second. The phone numbers are of course one-way hashed such that it is impossible to link a node’s identifier to an actual phone number. However we do have information about the country and region to which the node belongs (ie: country code / area code). While it is not inclusive of every call to and from the UK, it is estimated that the dataset includes approximately 80% of landline calls and 30% of mobile calls.

So my question to the complex systems / social network community is this: what are some questions we should attempt to ask of this dataset? Possible examples include calculating the strength of a particular region’s relationships with other regions and countries, analyzing the dynamics involved in “call cascades�, inferring the average size of an individual’s hierarchical social groups (from close friend to possible acquaintance), etc...

While many metrics may be impossible to calculate for a network of this magnitude, simple sampling can yield interesting results. For example, the plot above represents the duration of outgoing calls from 100,000 randomly sampled nodes during 6 month intervals over the course of October 1995 to March 1998. It is clear that there are an increasing number of very long calls (over 10^4.2 seconds ~ 4.5 hours) which could be a good indicator of the uptake of dial-up internet in the UK during this timeframe.

Posted by Nathan Eagle at 9:21 AM | Comments (3)

13 February 2006

The genetic basis (?) of political orientations

There was an interesting paper recently published in the American Political Science Review by Alford et al. that received a lot of attention, which asserted that political orientations have a major genetic component. This paper was done well, by behavioral genetic research standards, I think, a standard analysis of "concordance rates" of identical vs fraternal twins. I do want to pick at one important premise, which is that the strong correlation of political attitudes of identical (monozygotic) twins as compared to fraternal (dizygotic) twins is not due to greater communication and thus social influence between identical twins. Such an assertion is plausible, in that similarity typically predicts communication (homophily)—in fact, this is one of the most robust patterns in social network analysis. I would guess that identical twins see themselves as more similar than fraternal twins do (political orientations aside), and thus talk more. Note that I am unfamiliar with any research that actually demonstrates this (please comment if you are).

The authors do directly tackle this point (see p. 155), but, at first glance, at least, it is a weak reed they rest their assertion on, which is a paper by Martin et al. in 1986. ...

There was an interesting paper recently published in the American Political Science Review by Alford et al. that received a lot of attention, which asserted that political orientations have a major genetic component. This paper was done well, by behavioral genetic research standards, I think, a standard analysis of "concordance rates" of identical vs fraternal twins. I do want to pick at one important premise, which is that the strong correlation of political attitudes of identical (monozygotic) twins as compared to fraternal (dizygotic) twins is not due to greater communication and thus social influence between identical twins. Such an assertion is plausible, in that similarity typically predicts communication (homophily)—in fact, this is one of the most robust patterns in social network analysis. I would guess that identical twins see themselves as more similar than fraternal twins do (political orientations aside), and thus talk more. Note that I am unfamiliar with any research that actually demonstrates this (please comment if you are).

The authors do directly tackle this point (see p. 155), but, at first glance, at least, it is a weak reed they rest their assertion on, which is a paper by Martin et al. in 1986. This paper also examines whether identical twins have more similar attitudes than fraternal twins, based on UK and Australian twin sets, producing similar results. Frequency of communication between twins is not the primary focus of their paper. They devote all of two sentences to this issue (excerpt below):

…it is alleged that monozygotic twins see each other more frequently than dizygotic twins and that this greater frequency of contact is reflected in greater monozygotic similarity in attitudes. Since the correlation between reported frequency of contact and absolute intrapair difference in conservatism scores is -0.08 in female and -0.14 in male twin pairs in the Australian sample, any such effect must be trivial, even if the cause of such covariation is in the direction asserted.

As I see it, there are a few problems with this quick disposal of the issue:

(1) There is no explanation of how frequency is measured, so we cannot assess its validity. Further, timing of communication might matter quite a bit—one would guess that frequency of communication in late adolescence and early adulthood would matter a lot more in the formation of political attitudes than later (or earlier) in life. If they simply asked “how often do you talk with your twin,� the study, from a political socialization point of view, is aggregating a lot of apples and oranges.

(2) There is no effort to directly evaluate whether frequency even partially mediates the observed correlation differences between twin types. These are especially problems in view of the likely noisiness in both the political attitudinal and social interaction items. That is, they may be aggregating messy apples and oranges.

In short, this seems like a pretty weak falsification of the hypothesis that identical twins talk more than fraternal twins, and become more similar in political orientations because they talk, rather than being “inherently� similar due to genetic predispositions.

References:

John Alford, Carolyn Funk, and John R. Hibbing“Are Political Orientations Genetically Transmitted?� APSR (May 2005).
See http://www.apsanet.org/imgtest/GeneticsAPSR0505.pdf

Martin, N. G., L. J. Eaves, A. C. Heath, R. Jardine, L. M. Feingold, and H. J. Eysenck. 1986. “Transmission of Social Attitudes.� Proceedings of the National Academy of Sciences 15 (June): 4364–68.
See http://www.pnas.org/cgi/reprint/83/12/4364.

Posted by David Lazer at 3:00 PM | Comments (1)

12 February 2006

Longitudinal Data and the Adoption of Technology

I've spent this last week working on a paper with Kakuko Miyata and Barry Wellman. The paper uses longitudinal survey data collected in Japan to understand the causal relationship between the use of keitai (internet enabled mobile phones) and the reception of social support. This is one of the first opportunities that I've had to write a paper based on longitudinal data, and I'm thoroughly enjoying the experience. In addition to providing me with an understanding of the causal relationship between the technology and social behavior, the data is also allowing me to chart the adoption of a new technology, as it has become integrated into lives a general public. This experience has made me wonder about the extent to which the adoption of keitai is the result of a social network structure that is more prevalent in Japan than in countries. My hope is that more longitudinal studies of this nature will be conducted in different countries, so that I might someday better understand the extent to which adoption patterns are the result of differences in network structure, vs. other factors, such as culture, marketing, or investment in technological infrastructure.

Posted by Jeff Boase at 8:30 PM | Comments (2)

10 February 2006

The Strength of Weak Ties Revisited - A Practical Example

Having discussed Granovetter's seminal paper on "The Strength of Weak Ties" in our last class on Network Analysis, I just found a 21st century application of the theory on the website of Ideentower.blogs.com.

There is a relatively new service on the web, which allows people to connect to each other when traveling from A to B. The service is called AirTroductions and provides interested individuals to register and subsequently look for other, unknown individuals, that might be on the same flight. The purpose of the service is to allow people make interesting contacts which eventually lead to all type of relationships.

I found this interesting as another example for how easy it is today to build weak ties with modern web technology!

Posted by Thomas Langenberg at 11:14 PM | Comments (0)

7 February 2006

Structural vs. Relational Embeddedness: A useful Concept for Effective Knowledge Sharing within Firms?

In today's class on Network Analyis for Managers and Analysts we discussed how embeddedness matters for conducting transactions with friends, colleagues, or business partners. Since we attempted to make it an application driven class, we discussed managerial implications of the embeddedness concept a lot. We concluded that both relational ties and one's structural position in a network of personal contacts matter. Please find below some of the after-thoughts.

Building on our last entry, Hansen's search-and-transfer problem, we would like to highlight that effective knowledge creation and sharing is, among others, is dependent on one's structural and relational embeddedness in the organizational network. When analyizing knowledge sharing within firms, one might have to ask the following questions:

- Who are the persons that most effectively spread new throughout the organization. In every firm, there is an information communication network, which might be helpful to spread the news. What ist the structural embeddedness of the "communication hubs"?
- How do individuals within the organization think about sharing novel information? Are the knowledge "realms", do people tend to protect their personal knowledge, or is there an open communication atmosphere? What is the people relational embeddedness when it comes to information/knowledge sharing?

One can often see that firms spend huge amounts of money into knowledge management tools in order to foster knowledge sharing and creation. In many cases without even knowing how the (information) communuication network within the firms look like. Along these lines one might ask the question, whether or not awareness of the firm's (informal) communication networks can supplement at least parts of a big and expensive IT knowledge management infrastructure?

Posted by Thomas Langenberg at 10:18 PM | Comments (0)

Knowledge Networks: Knowledge Transfer within and between Organizations

In his 1999 paper on the "Search-and-Transfer" problem, Hansen introduced the notion of knowledge networks. In a product development context, Hansen finds that tie strength and knowledge tacitness moderate the ability of an organization to locate and exchange knowledge between organizational subunits.

Building on a current class discussion in the context of our latest course here at the Kennedy School, given by David Lazer(Network Analysis for Managers and Analysts), we have raised the question how feasible it might be to apply social network analysis for management and consulting purposes in industry. We asked whether or not it is possible to construct knowledge networks among firms by conducting a series of interviews in various firms.

A point we have really been discussing on is: To what extent will firms be willing and able to provide information about their knowledge search-and-transfer behavior in their inter- vs. intraorganizational knowledge networks?

The reference we use is:
Hansen, M. T. 1999. The Search-Transfer Problem: The Role of Weak Ties in Sharing Knowledge across Organization Subunits. Administrative Science Quarterly, 44(1): pp. 82-111

Posted by Thomas Langenberg at 12:30 AM | Comments (1)

5 February 2006

Contributions and Comments to our Blog: Some Clarifications

Dear Community of the Complexity and Social Network Blog,

Thank you very much to all of you who have tried to raise and drive this blog with your contributions and comments. We very much appreciate your efforts. It is important for us to build a strong community to make this blog an effective forum for discussions on "Complexity and Social Networks".

However, we feel that there is a need to send out a short message regarding the "rules and regulations" for the blog. In the past days we received quite a few comments on our blog entries regarding the latest developments in Europe and the Middle East (Click here for the link), which we unfortunately were not able to publish. We found the comments clearly politically and ideollogically motivated and did not refer to the blog's underlying theme (Complexity and Social Networks).

Our goal with this blog is NOT to facilitate discussions about more or less political issues. In our blog we want to disucss academic theories of "complexity and social networks", their application in the real world, and related research methodologies. In our latest blog entry for instance, we tried to apply an academic framework in a real life setting. In doing so, we attempted to facilitate a scholarly discussion on the effects of network structure on (organizational/institutioal) influence. Therefore, our blog does not provide a forum for discussion of political or religious issues. We think there are many other and probably much better places out there (on the internet) to do that.

Along these lines, we would like to thank you once again for your contributions, but please be aware of the fact that we cannot publish your posts when they become either too "political" or are not linked to the overall focus of this blog.

Regards,

Your PNG Blogging Team

Posted by Thomas Langenberg at 12:24 PM | Comments (0)

3 February 2006

Resisting network pressure or how to regain stability - Denmark vs. the Muslim Community

In the following entry, we attempt to become a little more substantial.

In the early phase of the current "Mohammed-Cartoon" episode, the discourse took place between the Danish publisher and the local Muslim community. However, now the news have spread and it has become a global debate. Yesterday, the UN (Kofi Annan) made a statement, individuals were threatend or taken hostage and governments are fearing economic and socio-political consequences (such as Denmark or France).

By taking a network perspective, we thus raise the following (research) question: How does a country's (structural) position in a global network of public and private sector organizations, NGO's, and a wide variety of civil society organizations impact its scope of political and economic action?

In 1997, Rowly published an article in the Academy of Management Review proposing a structural classification of stakeholder influences and potential organizational reactions. His conceptual framework looked as follows:

The following section represents a "thought experiment", and we are very aware of the fact that we take Rowley's framework and put in a slightly different context, which might not be 100% correct (academically speaking). Now let us assume that the global muslim community is a fairly well connected social network. At a very particular spot in this network, we will have Danish muslim community members interacting with Danish government and private sector entities. We further assume that (a) the number of Danish network entities is very small in comparison to the global network of muslim communities, and (b) Danish network entities maintain only a few ties to the muslim community, while the muslim community is building a lot of ties to Danish government or any other available entities for protesting. In summary, we assume that Denmark has a decentralized position in a dense network of muslim communities. The following figure shall depict this situation. White dots represent Danish government entitites and black dots represent muslim communities. The red arrow represents the origin of the debate between the publisher and the Danish muslim community. Also, see muslim community 11 and entity D. D has never been aware or in communication with 11. Neither is D closely connected to the core entities A, C and especially B. Now 11 is putting pressure on D (see the Danish embassy in Jakarta that was stormed today).

An adapted Rowley framework thus looks as follows.

In his paper, Rowley argues that under conditions of high network density (muslim community) and low centrality of the focal organization in the latter network, the focal organization (Denmark) is in a "vulnerable" position. He further argues that the structure of the community network allows for efficient communication, while "the focal organization is unable to influence the information exchange position from its peripherial position" (Rowley 1997, p. 903). In consequence, the focal organization is not in the position to resist network pressure.

The current situation seems to be pretty much the situation, the framework is trying to predict. While muslim communities are increasingly creating pressure on the Danish government, the country as a whole, currently, seems to have very little means to react and talk to any muslim community or sub-networks. However, also among the muslim community it is getting more difficult to influence the behaviour of entities/groups within the continuously expanding network on this issue.

Again, we would like to emphasize that we have utilized a highly theoretical framework to understand what is going on in the real world. The purpose of this entry is to conduct a thought experiment. We want to reflect on academic network theories by looking at real life contexts.

This blog is a collaborative effort with Alexander Schellong.

Posted by Thomas Langenberg at 2:12 AM | Comments (1)

2 February 2006

1 Entry, 2 sources and the world is reading - Danish / EU newspapers vs. the Islamic World

As a follow up to our entry on the Mohammed cartoons we would like to show you a map of the destinations our visitors came from in the past 24 hours. Apparently 2 link sources (1x Wikipedia article cited earlier, 1x bloglines) cause our blog to get attention from any continent. Europe and the US is dominating though. Well, we still hope to get some more comments from you on the past entry...

This is a joint post with Alexander Schellong.

Posted by Thomas Langenberg at 11:48 PM | Comments (0)

1 February 2006

Danish/ EU newspapers vs. the Islamic World - An Example of Network Failure?

12 Cartoons (Example 1, Example 2) posted in a Danish newspaper last September (10/30/2005) and thereafter caused a series of aftershocks which are felt now - 4 months later. Although the newspaper received a bomb threat right after the day of publishing and money was awarded for the execution of the cartoonist the real uprage just started this week with reports and reprints of the Mohammed cartoons all over Europe.

While we don't want to join the discussion on freedom of speech, making jokes about one's own God and the like, we would rather take a look at the network aspect of it. Although 11 amabassadors of islamic countries publicly protested about this and 5000 muslims marched through the streets of Copenhagen it took 3 months until this was fully recognized in the Arabic and international community. Why did it take so long, although media reported and all types of ICT's were utilized?

Let us take an "information diffusion" and "social network" perspective. One might argue that today social networks are so dense that information spreads quickly by any means (internet, blogs, wom etc), especially when the topic is potentially critical. According to our theories we would have expected that Arabic communities are very well connected so that news from Denmark rapidly diffused throughout the Islamic world. Also, we would have thought that ambassadors act as "information hubs" in their societies, and thus reactions would have occured much earlier.

So what happend to the "news" within the last 3 months? Did it take so long until a critical mass was built to react? Shall we assume that, based on powerlaw, it took 3 months to reach a consent within the strongest 20% of the Islamic community? Along these lines this would mean that 20% of the latter community gives us the feeling that the other 80% think simillarly. Is it really like that, or what might be other explanations for our observation?

International reports:
Wikipedia (very detailed)
CNN
BBC
Bloomberg
Brussels Journal
Die Welt blog (English)
Der Spiegel (German)

Arab Positions:
Arab News

This post is a collaborative effort with Thomas Langenberg.

Posted by Alexander Schellong at 2:44 PM | Comments (4)