Social networks and genomes join forces

Tracking transmission: Scientists used social-network analysis to find the origins of an outbreak of tuberculosis (top). A patient designated MT0001 was thought to be ground zero for the outbreak, with other patients represented as circles. After sequencing bacteria genomes, scientists could track how the microbes moved from person to person (bottom), and discovered that there were two independent outbreaks. Credit: New England Journal of Medicine

I read an interesting article today on ‘Technology Review’ titled ‘Social Networking’s Newest Friend: Genomics’. It describes a recently published study on the emergence and spread of TB in British Columbia. In order to pinpoint the source of the disease, scholars did not only trace whole-genomes of the microbes responsible, but they combined this with a survey of the affected medium-sized community. By mapping possible interactions between individuals and examining DNA sequences attested, they were able to track the disease back to two independent sources.

This is a clear example of how social networks can be relevant “in real-time” as the data becomes available, to solve real problems. If the sources of such diseases can be identified early on, then officials and the community can take measures to prevent it from spreading even more. It is generally accepted in epidemology that human networks are media for the spread of disease and network approaches have been very popular to understand such processes. By combining a networks approach with genomics, however, an innovative and extremely detailed picture can be painted of a disease’s passage through a community.

This research is not an exception to commonly accepted issues surrounding social network analysis, however. Although I do not doubt the researchers did a thorough survey of the population focusing on a diversity of parameters to construct their networks, the limitation of types of relationships to those that we think might be influential as well as the formalisation/quantification of such relationships remain a necessary evil. It is very hard with such an approach to stumble upon unconnected clusters or parameters that were not thought to be of influence, for example. Basic sampling issues. Also, the construction of a thoroughly qualified social network takes time! I very much doubt that such an approach can be performed at the same speed as the spread of many modern-day diseases.

Having said that, this is a beautiful example of how two largely unrelated perspectives can lead to a completely new approach that enhances the results of both.

Postgraduate conference Newcastle: Networks and scale

I just heard about this conference on Networks and Scale. The call for papers is out, deadline 1 April. Will definitely be of interest to archaeologists and historians interested in networks I believe. And I am planning on sending in a paper myself.

Call for Papers

‘Networks and Scales: Relating the local and the global’

Newcastle University, 23 May 2011

This interdisciplinary conference seeks to address the notion of network across boundaries and disciplines. Are we aware of the networks within which our subjects exist? Do we address sufficiently issues of network and scale in the past? How do we make connections between the often narrow focus of doctoral research and the local and global scales within which we practice?

We invite papers which address issues of networks and scale, local and global, within past and present. For example:

* Research which transcends boundaries

* Person-Place-Thing relations

* Local studies and their wider impact

* Issues of scale throughout time

* Global connections

Abstracts to be submitted to by 1 April 2011.

General enquiries can be forwarded to the conference organisers, Melinda Sutton, Sophie Moore and Rachel Crellin at the same address.

“leaderless revolutions” in modern Egypt and … the past??

I just read this fascinating blog post by Zeynep Tufekci, assistant professor in sociology at the University of Maryland, Baltimore county. She states that through the democratic nature of the recent revolution in Egypt a hierarchy emerged. A fundamentally leaderless situation gave rise to popular leadership. According to the author this can be explained by the “rich get richer” effect, and she illustrates this with how People on Twitter using the hashtag ‘Jan25’ shows a scale-free power law. Apparently, those people tweeting about the revolution that have alot of followers will end up getting ever more followers. They have become the (digital) leaders of a headless revolutionary event. I find it interesting how this hierarchy and its immediate effects must have been the result of a critical mass of influence reaching a turning point, leading to revolutionary events.

Obviously Twitter is only one medium through which ideas can be spread, and in no way does the “rich get richer” effect explain WHY the revolution happened. What were the individual motivations that led to this large-scale event? What the scale-free model does imply, however, is that the event could not have taken place without these individuals and their actions, their decisions to follow increasingly popular charismatic (albeit digital) figures.

Could this perspective help us understand past revolutions?

Obviously ideas spread much slower in the past than in the present. But that does not mean that revolutions happened any slower or less spontaneous. How could we explore past revolutions through the material remains that we examine as archaeologists? I would be very interested in seeing how changes in material culture attest of a scale-free pattern. A perfect example is Bentley and Shennan’s work on Linear Bandkeramik in Germany. They showed that the patterns on these vessel evolved according to a scale-free power law, where popular motifs were expected to become ever more popular and more influential in future motif design. What fascinates me about this kind of research is that it does not incorporate any measure of originality in innovation. Motifs or ideas might not have been all that revolutionary, for example, but for some reason they became popular and widely adopted. Through them revolutions emerged, more as a result of their relation to other things/people/ideas than their inherent qualities. Still, the question of why this scale-free structure emerges and shapes revolutions remains unanswered. And what about truly revolutionary ideas? Does their adoption show a scale-free structure? And if not, is that really the reason why they did not catch on?

ego-networks on LinkedIn and Facebook

LinkedIn just released a new feature: the InMap. It’s a tool that allows you to visualise all your contacts, and the relationships between them. In social network analysis terms that would be called an ‘ego-network’, where the ego is an individual (you in this case) and the network includes all of the ego’s relations and the relations between them. There are a number of apps available that allow you to do the same thing for Facebook.

One of the coolest features of these network visualisations is that they display clusters of friends that are strongly related in different colours. Although this is an automatic feature based on a simple algorithm, it manages to pick out meaningful groupings. In my case, for example, all my colleagues at the department of Archaeology here at the University of Southampton are grouped, another grouped are my fellow students from the University of Leuven and yet another one are my friends from the town where I grew up, Antwerp. With these groups you can identify professional alliances or groups of friendships which you might want to reinforce.

From this example you might gather that most of these groups have some sort of geographical logic behind them: you will be more likely to be friends with people you meet in person every day. Also, some clusters exist of people affiliated with the same institutions like universities. Although this might sound like a banal conclusions, it has two very interesting implications: physical proximity matters in creating (digital) friendships and, more importantly, is all but dominant for the evolution of your relationships. You will notice, for example, how some of your friends are actually bridging two groups, which made me think about how those two people actually got in touch in the first place. Was it through me? Or did I have nothing to do with their friendship? If so, how did their pre-existing friendship influence my choice of friends?

Have a look at your own ego-networks for LinkedIn and Facebook, and be surprised!

Facebooking the past (draft)

I recently finished a first draft of the paper I presented at TAG in Bristol last December. It discusses the assumptions and issues surrounding the use of Social Network Analysis for Archaeology. I like to believe that the paper is very readable. It starts with a short fiction about Cicero who used Facebook and Twitter from his iPhone 4 to become consul of Rome … in 63BC. This story becomes relevant in the latter part of the paper, however, where I stress the importance of realising that when we think through a networks perspective we assume that networks must have existed in the past.

I would love any kind of feedback on this working paper! You can download it from the bibliography page (first one in the list).


Facebook currently has over 500 million active users, only six years after its launch in 2004. The social networking website’s viral spread and its direct influence on the everyday lives of its users troubles some and intrigues others. It derives its strength in popularity and influence through its ability to provide a digital medium for social relationships.

This paper is not about Facebook at all. Rather, through this analogy the strength of relationships between people becomes apparent most dramatically. Undoubtedly social relationships were as crucial to stimulating human actions in the past as they are in the present. In fact, much of what we do as archaeologists aims at understanding such relationships. But how are they reflected in the material record? And do social network analysis techniques aimed at understanding such relationships help archaeologists understand past social relationships?

This paper explores the assumptions and issues involved in applying a social network perspective in archaeology. It argues that the nature of archaeological data makes its application in archaeology fundamentally different from that in social and behavioural sciences. As a first step to solving the identified issues it will suggest an integrated approach using ego-networks, popular whole-network models, multiple networks and affiliation networks, in an analytical process that goes from method to phenomena and back again.

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