Lord of the Rings, Disney’s Mulan and the stuff I do: it’s all the same

February 2, 2015

Yes, there are similarities between my work and things that people actually want to spend time listening to. But you really have to look hard for them. I’ve given a lot of presentations over the last few years and noticed that one of the best ways of getting a difficult idea across is to use a movie analogy. I also learned I was very bad at preparing my presentation in time to think up movie analogies. So here’s a blog post to make up for it, inspired by a new paper I wrote that just came out in Journal of Archaeological Method and Theory. My work is a bit like Lord of the Rings and Mulan.

But not in the way you hope it is. There is nothing near as exciting in my research as the cavalry charges in both those movies, and I definitely never experienced a ‘montage’ moment that provided me in a ridiculously short timespan with the crazy skills needed to destroy the baddie.

What my work has in common with both Mulan and Lord of the Rings are fire signals. This video shows the memorable scene from Return of the King when the fire beacons in Gondor are lit, triggering the lighting of a chain of other beacons. The message is clear and reaches its target quickly: Gondor looks to Rohan for help.

The opening scene of Disney’s Mulan is similar: when the bad guys attack, beacons are lit all along the great wall of China to warn the Chinese people of the coming threat.

These scenes are not completely unthinkable fantasy scenarios, but are inspired by early communication systems that actually existed in the past. In times before telephones and telegraphs, signalling systems using fire, smoke, sound or light could have been used to spread messages over very long distances.

Archaeologists studying the Iron Age of Spain believe such a communication system might have existed in some regions. And it is easy to understand why. The settlement pattern in much of Spain during the Iron Age was dominated by large fortified urban settlements on hills, hence they are sometimes referred to as hillforts. These large urban settlements were surrounded by smaller rural settlements. The surrounding landscape could be visually controlled from many of these hillforts, and the hillforts were visually prominent features that could be seen from far away.

Now what scene of Lord of the Rings does this remind me of? That’s right: the Eye of Sauron perched on top of the massive tower of Barad Dur, scanning the surrounding landscape for his enemies, and to his followers acting as a visible reminder of who’s boss.

Many archaeologists believe these large urban settlements were located on hills on purpose, and not just because a hill was easier to defend but because of the views it offered: visually controlling the landscape, being visually prominent from its surroundings and acting as a good link in a fire signalling network.

And this is where networks come in! If archaeologists argue that settlements might have been located with visibility in mind for the three reasons mentioned here, then we should approach these statements as hypotheses that need testing. And we can do that in three ways using network science:

1) visualise the network of inter-visible settlements using our knowledge of the settlement pattern;
2) explore its structure to see whether it would function well as a communication network, or whether some settlements are more visually prominent;
3) simulate a process where places are settled so that a well-functioning communication network and/or a few more visually prominent settlements is established, and compare this simulated settlement pattern with the observed one.

This is what I do. The first approach uses network data representation and network layout algorithms to show a network of inter-visible settlements, and explore this pattern in a new way by extracting it from its geographical context and focusing just on its structure for a change. The second approach then uses exploratory network analysis techniques that tell us something more about individual nodes in the network and about the network as a whole (e.g. identify most visually prominent settlements, identify chains of inter-visible settlements). The third approach is in my eyes the most interesting one because it is totally new: using simulation models we generate millions of networks according to the process we hypothese might have taken place and we compare the simulated networks with the oberved ones using the same exploratory network analysis techniques as in the second approach.

This new approach to simulating our hypotheses about visibility networks is called exponential random graph modelling for visibility networks. A pair of papers just came out in which we introduce this method and apply it to Iron Age and Roman Southern Spain. The results are really interesting: there is no evidence for a well-functioning communication network, but there is definitely reason to believe that the pattern of visually prominent settlements that visually control surrounding rural settlements was purposefully established in the Iron Age. The importance of visibility as a factor determining settlement location then gradually decreases throughout Roman times.

Our recently published paper in Journal of Archaeological Method and Theory tells you the full story. The method is explained in detail in our paper in Journal of Archaeological Science. Both are available through my Academia.edu page or my bibliography on this blog. Enjoy!

The networks they are a-changin’: introducing ERGM for visibility networks

July 17, 2014

legosIn my madness series of posts published a few months ago I mentioned I was looking for a method to study processes of emerging intervisibilty patterns. I can finally reveal this fancy new approach to you 🙂 Here it is: introducing exponential random graph modelling (ERGM) for visibility networks. In previous posts I showed that when archaeologists formulate assumptions about how lines of sight affected past human behaviour, these assumptions imply a sequence of events rather than a static state. Therefore, a method is needed that allows one to test these assumed processes. Just analysing the structure of static visibility networks is not enough, we need a method that can tackle changing networks. ERGM does the trick! I just published a paper in Journal of Archaeological Science with Simon Keay and Graeme Earl that sets out the archaeological use of the method in detail. You can download the full paper on ScienceDirect, my Academia page or via my bibliography page. But in this blog post I prefer to explain the method with LEGOs 🙂



Social network analysts often use an archaeological analogy to explain the concept of an ERGM (e.g., Lusher and Robins 2013, p. 18). Past material remains are like static snapshots of dynamic processes in the past. Archaeologists explore the structure of these material residues to understand past dynamic processes. Such snapshots made up of archaeological traces are like static fragmentary cross-sections of a social process taken at a given moment. If one were to observe multiple cross-sections in sequence, changes in the structure of these fragmentary snapshots would become clear. This is exactly what an ERGM aims to do: to explore hypothetical processes that could give rise to observed network structure through the dynamic emergence of small network fragments or subnetworks (called configurations). These configurations can be considered the building blocks of networks; indeed, LEGO blocks offer a good analogy for explaining ERGMs. To give an example, a network’s topology can be compared to a LEGO castle boxed set, where a list of particular building blocks can be used to re-assemble a castle. But a LEGO castle boxed set does not assemble itself through a random process. Instead, a step by step guide needs to be followed, detailing how each block should be placed on top of the other in what order. By doing this we make certain assumptions about building blocks and their relationship to each other. We assume that in order to achieve structural integrity in our LEGO castle, a certain configuration of blocks needs to appear, and in order to make it look like a castle other configurations will preferentially appear creating ramparts, turrets, etc. ERGMs are similar: they are models that represent our assumptions of how certain network configurations affect each other, of how the presence of some ties will bring about the creation or the demise of others. This is where the real strength of ERGMs lies: the formulation and testing of assumptions about what a connection between a pair of nodes means and how it affects the evolution of the network, explicitly addressing the dynamic nature of our archaeological assumptions.

More formally, exponential random graph models are a family of statistical models originally developed for social networks (Anderson et al. 1999; Wasserman and Pattison 1996) that aim to scrutinize the dependence assumptions underpinning hypotheses of network formation by comparing the frequency of particular configurations in observed networks with their frequency in stochastic models.

The figure below is a simplified representation of the creation process of an ERGM. (1a) an empirically observed network is considered; (1b) in a simulation we assume that every arc between every pair of nodes can be either present or absent; (2) dependence assumptions are formulated about how ties emerge relative to each other (e.g. the importance of inter-visibility for communication); (3) configurations or network building blocks are selected that best represent the dependence assumptions (e.g. reciprocity and 2-path); (4) different types of models are created (e.g. a model without dependence assumptions (Bernoulli random graph model) and one with the previously selected configurations) and the frequency of all configurations in the graphs simulated by these models is determined; (5) the number of configurations in the graphs simulated by the models are compared with those in the observed network and interpreted.


My madness series of posts and the recently published paper introduce a case study that illustrates this method. Iron Age sites in southern Spain are often located on hilltops, terraces or at the edges of plateaux, and at some of these sites there is evidence of defensive architecture. These combinations of features may indicate that settlement locations were purposefully selected for their defendable nature and the ability to visually control the surrounding landscape, or even for their inter-visibility with other urban settlements. Yet to state that these patterns might have been intentionally created, implies a sequential creation of lines of sight aimed at allowing for inter-visibility and visual control. An ERGM was created that simulates these hypotheses. The results suggest that the intentional establishment of a signalling network is unlikely, but that the purposeful creation of visually controlling settlements is better supported.

A more elaborate archaeological discussion of this case study will be published very soon in Journal of Archaeological Method and Theory, so stay tuned 🙂 Don’t hesitate to try out ERGMs for your own hypotheses, and get in touch if you are interested in this. I am really curious to see other archaeological applications of this method.

References mentioned:

Anderson, C. J., Wasserman, S., & Crouch, B. (1999). A p* primer: logit models for social networks. Social Networks, 21(1), 37–66. doi:10.1016/S0378-8733(98)00012-4

Lusher, D., Koskinen, J., & Robins, G. (2013). Exponential Random Graph Models for Social Networks. Cambridge: Cambridge university press.

Lusher, D., & Robins, G. (2013). Formation of social network structure. In D. Lusher, J. Koskinen, & G. Robins (Eds.), Exponential Random Graph Models for Social Networks (pp. 16–28). Cambridge: Cambridge University Press.

Wasserman, S., & Pattison, P. (1996). Logit models and logistic regressions for social networks: I. An introduction to Markov graphs and p*. Psychometrika, 61(3), 401–425.

Portus and ACRG work on BBC 1

December 11, 2012

Visualisation of Harbour produced by BBC for Rome’s Lost Empire in collaboration with Portus Project

Visualisation of Harbour produced by BBC for Rome’s Lost Empire in collaboration with Portus Project

On Sunday a show called Rome’s Lost Empire featured loads of great work by Southampton archaeologists. Since 2007 a team led by Prof. Simon Keay and Dr. Graeme Earl has been excavating at Portus, the port of the city of ancient Rome. The BBC 1 show reveals some of their latest findings, as well as the 3D modelling work of our Archaeological Computing Research Group team.

You can watch the show on BBC iPlayer.

Read more about the computer models that were created for this show on the Portus blog. There you can also read a message by Prof. Simon Keay about the show.

Arts, Humanities, and Complex Networks ebook now out!

April 12, 2012

Leonardo (the International Society for the Arts, Sciences and Technology) and MIT Press produced a new ebook that confirms the Arts and Humanities finally form a valuable part of the growing group of disciplines often associated with complex network research. The ebook edited by Maximilian Schich, Roger Malina and Isabel Meirelles is a collection of 26 short articles based on presentations at the Arts, Humanities, and Complex Networks Leonardo Days at the NetSci conferences, the High Throughput Humanities conference, and most were previously published in Leonardo journal. The works by specialists in fields as diverse as archaeology, history, music, visualisation and language studies illustrate that the Arts and Humanities can make original contributions to complex network research and provide fascinating new perspectives in a wide range of disciplines. A nice online companion was launched together with the ebook.

The volume includes two contributions by researchers from The University of Southampton: the Google Ancient Places project is discussed by Leif Isaksen and colleagues, and the Urban Connectivity in Iron Age and Roman Southern Spain project was introduced by Simon Keay, Graeme Earl and myself. You can find a draft of that last article on my bibliography page.

You can order the ebook on Amazon.

Do check it out!

Here is the full table of contents:

Preface by Roger Malina
Introduction by Isabel Meirelles and Maximilian Schich

I Networks in Culture

Networks of Photos, Landmarks, and People
David Crandall and Noah Snavely

GAP: A NeoGeo Approach to Classical Resources
Leif Isaksen et al.

Complex Networks in Archaeology: Urban Connectivity in Iron Age and Roman Southern Spain
Tom Brughmans, Simon Keay, and Graeme Earl

II Networks in Art

Sustaining a Global Community: Art and Religion in the Network of Baroque Hispanic-American Paintings
Juan Luis Suárez, Fernando Sancho, and Javier de la Rosa

Marek Claassen

When the Rich Don’t Get Richer: Equalizing Tendencies of Creative Networks
John Bell and Jon Ippolito

The Mnemosyne Atlas and The Meaning of Panel 79 in Aby Warburg’s Oeuvre as a Distributed Object
Sara Angel

Documenting Artistic Networks: Anna Oppermann’s Ensembles Are Complex Networks!
Martin Warnke and Carmen Wedemeyer

Net-Working with Maciunas
Astrit Schmidt-Burkhardt

Network Science: A New Method for Investigating the Complexity of Musical Experiences in the Brain
Robin W. Wilkins et al.

Networks of Contemporary Popular Musicians
Juyong Park

III Networks in the Humanities

The Making of Sixty-Nine Days of Close Encounters at the Science Gallery
Wouter Van den Broeck et al.

Social, Sexual and Economic Networks of Prostitution
Petter Holme

06.213: Attacks with Knives and Sharp Instruments: Quantitative Coding and the Witness To Atrocity
Ben Miller

The Social Network of Dante’s Inferno
Amedeo Cappelli et al.

A World Map of Knowledge in the Making: Wikipedia’s Inter-Language Linkage as a Dependency Explorer of Global Knowledge Accumulation
Thomas Petzold et al.

Evolution of Romance Language in Written Communication: Network Analysis of Late Latin and Early Romance Corpora
Alexander Mehler et al.

Need to Categorize: A Comparative Look at the Categories Of Universal Decimal Classification System and Wikipedia
Almila Akdag Salah et al.

The Development of the Journal Environment of Leonardo
Alkim Almila Akdag Salah and Loet Leydesdorff

IV Art about Networks

Tell Them Anything but the Truth: They Will Find Their Own. How We Visualized the Map of the Future with Respect to the Audience of Our Story
Michele Graffieti et al.

Model Ideas: From Stem Cell Simulation to Floating Art Work
Jane Prophet

Culture, Data and Algorithmic Organization
George Legrady

Cybernetic Bacteria 2.0
Anna Dumitriu

Narcotic of the Narrative
Ward Shelley

V Research in Network Visualization

Building Network Visualization Tools to Facilitate Metacognition Incomplex Analysis
Barbara Mirel

Pursuing the Work of Jacques Bertin
Nathalie Henry Riche

Slides of presentations online folks

June 9, 2011

You can now download the slides from my recent presentations in Newcastle, Southampton, Leuven, Budapest and my presentation tomorrow in Vienna from my bibliography page. I know they are all very similar, but there are some slight variations. Task: find the 10 differences between them 🙂

If you want to read the research underlying this you will have to wait a bit longer because we are still writing it out. But you can always check out the abstracts (added as description on Scribd). And if you really can’t wait just send me an e-mail and I will give you a sneak-preview!

And finally I would like to give you a last-minute reminder of the workshop in Vienna tomorrow titled “Connecting the dots. The analysis of networks and the study of the past (Archaeology and History)”. It’s a half-day Workshop on 10 June 2011 at the Institut für Byzanzforschung (IBF), Österreichische Akademie der Wissenschaften. Check out the invitation here.