Book: support networks for persecuted Jews in WWII

9783110368949I find support and assistance networks extremely interesting! Mainly because they pose so many interesting missing data problems, and as an archaeologist I like a good data problem from time to time. These kinds of networks are very much based on trust, since once a person or connection is compromised it will have disastrous, often murderous, consequences for many in the network. This topic is explored for the case of persecuted Jews in National Socialism during World War II in Marten Düring’s work. He traced a number of different groups of people, how they got in touch with each other, and how they provided assistance to persecuted Jews. Marten told me in most cases the support networks grow slowly and are built on strong trusted relationships. Often new individuals will be introduced to the network through a common contact who has received assistance before and vouches for the individual. However, there are a few cases when individuals gambled and got in touch without a pre-existing well-trusted connection. Such decisions could be disastrous, sometimes leading to the entire network being rounded up by the Gestapo, questioned and sentenced (which is often why these support networks are documented and why Marten was able to reconstruct them). The ‘data problems’ I mentioned are a consequence of the sheer secretive nature of the support network: hiding the fact you offered support to persecuted Jews was a question of life or death. It is particularly hard to reconstruct support networks that were not caught by the Gestapo, and one can only assume that those that were caught are not entirely documented, that there are a lot of missing nodes and links. Marten Düring offers us an in-depth look at a few cases which are particularly well-known, thanks to his rummaging around in archives for years.

I believe this study will prove invaluable for better understanding support networks and the missing data problems they pose. I see particular similarities with networks of the trade in licit antiquities, organized crime and really any type of so-called ‘dark network’. This work offers a reminder of how the study of the past can help us tackle challenges in the present.

Marten’s work was recently published by De Gruyter as a book, check it out here and find the abstract below.

Also keep an eye out for Marten’s chapter in the forthcoming ‘The Connected Past’ edited volume to be published by Oxford University Press early in 2016 🙂

Why did people help Jews hide from the Nazis? This study examines interactions between helpers and aid recipients using the methods of social network research. Based on six Berlin case studies, the author looks at the social determinants for willingness to help, trust formation, network effects, and the daily practice of providing help from the perspectives of helpers and aid recipients.

It’s that conference season again!

This month is just raining interesting conferences again! If you’re into the kind of research I like that is: social simulation, The Connected Past, and Historical Networks Research … Ooooooh Yeeeeaaah! 🙂

Two weeks ago I was in Barcelona for the Social Simulation Conference and the Simulating the Past satellite conference. Reports of this event on my blog did not get beyond part 1. That’s just because Barcelona is so much fun and it would be a shame to sit in a hotel room writing blog posts any longer than I already did. The conference was great overall. There was a surprising number of talks presenting a project outline rather than results. Although conferences are good places to recruit people on such projects, these talks are not always as engaging as others.

Ulrik Brandes giving a keynote presentation at TCP London
Ulrik Brandes giving a keynote presentation at TCP London

Last week I co-organised The Connected Past with Tim Evans and Ray Rivers at Imperial College London, and the rest of the Connected Past team. It strikes me as a wonderful thing how every time we organise an event we attract a truly multi-disciplinary, young, and curious audience. Interestingly there is also always a slight majority of female scholars at The Connected Past events, which is very welcome given that in academia often the opposite is true. Our audience is always a particularly studious bunch. Humanities scholars looking to learn more about what that network thing is all about, and scholars from the hard sciences who want to know if they can jump on a research topic/problem/dataset that is slightly more sexy than gravity. The keynote talks by Alan Wilson, Ulrik Brandes and Joaquim Fort were brilliant! Each drew from their personal experiences of applying a different computation modelling approach to archaeological research: agent-based modelling, network modelling, and statistical modelling. In particular, I can recommend Brandes’co-authored paper entitled ‘what is network science?’, which is definitely required reading for anyone following this blog. I am sure this is not gonna be the last Connected Past event. In fact, I’ll be able to announce some cool TCP news very soon I hope.

This week it’s time for Historical Networks Research, an initiative that already received loads of blogspace here. No need to break the trend: expect reports from the keynotes and talks as the conference progresses over the coming days. I am particularly looking forward to the keynote by Claire Lemercier, who organised a fantastic TCP in Paris in April. Claire is a real pioneer in applying network science in history, and her review article on the subject is a must-read for any historians interested in networks. Stay tuned for more on Historical Networks Research soon!

Problems with archaeological networks part 1

Plate_of_SpaghettiAs I mentioned before, I recently published a review of formal network methods in archaeology in Archaeological Review from Cambridge. I want to share the key problems I raise in this review here on my blog, because in many ways they are the outcomes of working with networks as an archaeologist the last six years. And yes, I encountered more problems than I was able to solve, which is a good thing because I do not want to be bored the next few years 🙂 In a series of four blog posts I draw on this review to introduce four groups of problems that archaeologists are faced with when using networks: method, data, space process. The full paper can be found on Academia. This first blog post in the series discusses methodological issues, enjoy 🙂

Like any other formal techniques in the archaeologist’s toolbox (e.g. GIS, radiocarbon dating, statistics), formal network techniques are methodological tools that work according to a set of known rules (the algorithms underlying them). These allow the analyst to answer certain questions (the network structural results of the algorithms), and have clear limitations (what the algorithms are not designed to answer). This means that their formal use is fundamentally limited by what they are designed to do, and that they can only be critically applied in an archaeological context when serving this particular purpose. In most cases, however, these formal network results are not the aim of one’s research; archaeologists do not use network methods just because they can. Instead one thinks through a networks perspective about the past interactions and systems one is actually interested in. This reveals an epistemological issue that all archaeological tools struggle with: there is a danger that formal networks are equated with the past networks we are trying to understand (Isaksen 2013; Knox et al. 2006; Riles 2001). In other cases, however, formal analysis is avoided altogether and concepts adopted from formal network methods are used to describe hypothetical past structures or processes (e.g. Malkin 2011). Although this sort of network thinking can lead to innovative hypotheses, it is not formal network analysis (see reviews of Malkin (2011) by Ruffini (2012) and Brughmans (2013)). However, such concepts adopted from formal network methods often have a very specific meaning to network analysts and are associated with data requirements in order to express them. Most crucially, when the concepts one uses to explain a hypothesis cannot be demonstrated through data (not even hypothetically through simulation), there is a real danger that these concepts become devalued since they are not more probable than any other hypotheses. Moreover, the interpretation of past social systems runs the risk of becoming mechanised when researchers adopt the typical interpretation of network concepts from the SNA or physics literature without validating their use with archaeological data or without modifying their interpretation to a particular archaeological research context. This criticism is addressed at the adoption of formal network concepts only. It should be clear that other theoretical concepts could well use a similar vocabulary whilst not sharing the same purpose or data requirements, in which case I would argue to refrain from using the same word to refer to different concepts or explicitly address the difference between these concepts in order to avoid confusion.

Although it is easy to claim that the rules underlying formal network techniques are known, it is less straightforward to assume that the traditional education of archaeologists allows them to decipher these algorithms. Archaeologists are not always sufficiently equipped to critique the mathematical underpinnings of network techniques, let alone to develop novel techniques tailor-made to address an archaeological question. For many archaeologists this means a real barrier or at least a very steep learning curve. Sadly, it also does not suffice to focus one’s efforts on the most common techniques or on learning graph theory. Like GIS, network analysis is not a single homogeneous method: it incorporates every formal technique that visualises or analyses the interactions between nodes (either hypothetical or observed), and it is only the particular nature of the network as a data type that holds these techniques together (Brandes et al. 2013). For this purpose it draws on graph theory, statistical and probability theory, algebraic models, but also agent-based modelling and GIS.

A thorough understanding of the technical underpinnings of particular network techniques is not an option; it is a prerequisite for a critical interpretation of the results. A good example of this is network visualisation. Many archaeologists consider the visualisation of networks as graphs a useful exploratory technique to understand the nature of their data, in particular when combined with geographical visualisations (e.g. Golitko et al. 2012). However, there are many different graph layout algorithms, and all of them are designed for a particular purpose: to communicate a certain structural feature most efficiently (Conway 2012; Freeman 2005). These days, user-friendly network analysis software is freely available and most of it includes a limited set of layouts, often not offering the option of modifying the impact of variables in the layout algorithms. Not understanding the underlying ‘graph drawing aesthetics’ or limiting one’s exploration to a single layout will result in routinized interpretations focusing on a limited set of the network’s structural features.

Archaeologists who consider the application of network methods to achieve their research aims must be able to identify and evaluate such issues. Multi-disciplinary engagement or even collaboration significantly aids this evaluation process.

References:
Brandes, U., Robins, G., McCranie, A., & Wasserman, S. (2013). What is network science? Network Science, 1(01), 1–15. doi:10.1017/nws.2013.2
Brughmans, T. (2013). Review of I. Malkin 2011. A Small Greek World. Networks in the Ancient Mediterranean. The Classical Review, 63(01), 146–148. doi:10.1017/S0009840X12002776
Conway, S. (2012). A Cautionary Note on Data Inputs and Visual Outputs in Social Network Analysis. British Journal of Management. doi:10.1111/j.1467-8551.2012.00835.x
Freeman, L. C. (2005). Graphic techniques for exploring social network data. In P. J. Carrington, J. Scott, & S. Wasserman (Eds.), Models and methods in social network analysis (Vol. 5, pp. 248–268). Cambridge: Cambridge University Press. doi:10.3917/enje.005.0059
Golitko, M., Meierhoff, J., Feinman, G. M., & Williams, P. R. (2012). Complexities of collapse : the evidence of Maya obsidian as revealed by social network graphical analysis. Antiquity, 86, 507–523.
Isaksen, L. (2013). “O What A Tangled Web We Weave” – Towards a Practice That Does Not Deceive. In C. Knappett (Ed.), Network analysis in archaeology. New approaches to regional interaction (pp. 43–70). Oxford: Oxford University Press.
Knox, H., Savage, M., & Harvey, P. (2006). Social networks and the study of relations: networks as method, metaphor and form. Economy and Society, 35(1), 113–140. doi:10.1080/03085140500465899
Malkin, I. (2011). A small Greek world: networks in the Ancient Mediterranean. Oxford – New York: Oxford University Press.
Riles, A. (2001). The Network inside Out. Ann Arbor, MI: University of Michigan Press.
Ruffini, G. (2012). Review of Malkin, I. 2011 A Small Greek World: Networks in the Ancient Mediterranean. American Historical Review, 1643–1644.

A thousand worlds: sci-fi networks in archaeology

Rune Rattenborg presenting at 'A Thousand Worlds' in Durham
Rune Rattenborg presenting at ‘A Thousand Worlds’ in Durham
Here is a common plot in sci-fi literature and movies (based on a popular physics model): the world you know is but one in an endless range of parallel universes, where each one is slightly different. Who would ever have thought this would be a good starting point for archaeological discussions? Yet the meeting in Durham I recently attended showed that parallel universes might have more in common with archaeology than we think.

(this review was originally published as a guest post on Electric Archaeology, please join discussion there)

I was invited by Rune Rattenborg to join a workshop in Durham called ‘A Thousand Worlds: Network Models in Archaeology’. This concept of a thousand worlds can be interpreted in an archaeological research context in different ways. On the one hand, and most similar to the sci-fi parallel universes plot, you could think about the many different reconstructions of past realities that could all explain a single archaeological pattern. Literally thousands of hypotheses could be raised to explain a certain pattern, each of them suggesting different mechanisms driving human behaviour and ultimately its expression in the archaeological record. On the other hand, you could think about the many academic perspectives archaeologists find useful for understanding the past. Perspectives ranging from highly quantitative (you can place me in that camp) to very qualitative, from local to global, from scientific to philosophical, and from an explicitly present-day perspective to attempting to recreate past perspectives. Each one of these is a valid way of thinking about past human behaviour and behavioural change (or rather every configuration or combination of these perspectives).

Both of these interpretations motivated Rune to title his workshop ‘A Thousand Worlds’. He noticed that archaeologists interested in questions of past connectivity and those of us using network perspectives often address the challenges we are faced with in very different ways. The only common ground of most network perspectives seems to be that the relationships between entities are considered crucial to understanding the behaviour of these entities. For example, the romantic relationship between two individuals will affect the decision to stay in and watch a Hugh Grant romantic comedy or to go out for a beer with the guys. But Rune also noticed that each perspective allows for a wide variety of reconstructions of past realities. These two issues seem to confuse archaeologists who might be interested in using such a network perspective in their archaeological research. I totally agree with Rune’s motivation to create some order in this chaos. The main questions of this workshop therefore were: what different network perspectives are out there? What rules govern them? What do they allow us to do that we could not do before? And what are their limitations?

To some extent the meeting was successful in addressing these questions. A number of very different perspectives were discussed by selected proponents: I introduced an extremely formal network science approach, which was discussed rather more pragmatically by Anna Collar; Michelle de Gruchy highlighted some interesting challenges in a geographical context; another group of presenters (Kristoffer Damgaard, Eivind Heldaas Seland, Sofie Laurine Albris, Rune Rattenborg) used the concept of connectivity and explored how it could be reflected in archaeological and literary sources. Finally Ronan O’Donnell introduced the actor-network theory (ANT) perspective through a fascinating case study on a post-Medieval landscape in Northumberland, UK, from which the strong difference between the aims of the ANT and network science research perspectives became particularly clear.

Nevertheless, by the end of the meeting it became clear that we were not entirely successful in addressing the many questions we set out to answer. Eivind Heldaas Seland skilfully summarised each paper and formulated three key questions that require more attention: how can these different perspectives and approaches usefully work together? What is the added value of some of these compared to a more traditional description of our sources? How can we better use these perspectives in the future? The fact that we were unsuccessful at addressing these questions shows how complex and non-trivial they are (and we also ran out of discussion time). But for what it’s worth, I take this opportunity to share some of my thoughts on these questions, combined with some of the points I picked up from others during the discussion.

First of all, I believe the first question presents the false impression that the different network perspectives can and need to work together. I would argue that, many network perspectives do not need to and most of them do not work well together at all. This is because some of them (like ANT and network science) are designed to address very different questions. But even those approaches that have more in common, like the quantitative vs. qualitative use of network science, don’t necessarily need to be combined into an almighty network approach. There is no need for a great unifying theory or method in archaeology, not even for one that just focuses on questions of connectivity. Rather, I consider the different network perspectives as tools that function according to certain rules, and once these rules are known the tools have a potential to make small but crucial contributions to our knowledge of the past. I believe that if we are to ever achieve the full potential of these exciting new approaches for archaeology we will need to first critically explore them in isolation.

Secondly, the added value of these perspectives is more obvious than how they should be applied. Many in the audience seemed to agree that the concept of the network itself is a powerful tool to think with. It forces us to consider the potentially important role played by relationships between entities (however defined: humans, molecules, parallel universes), which might allow us to ask and answer new questions. For me the added value lies in the recognition that all archaeologists make assumptions about the nature of such relationships when they formulate hypotheses about past phenomena. It can be useful to think about these assumptions in terms of network concepts and, most importantly, there is a real need to be critically aware of their existence and formulate them clearly. Network science can help archaeologists to think about their assumptions of past relationships, to formally express them (in words and/or in numbers), and to evaluate their implications for past behavioural change and its reflection in the archaeological record.

Finally, the “better use” of such approaches and perspectives is not optional, it is necessary if they are ever to become useful within an archaeological research context. However, a critical use and application is not just a critical awareness of the rules that govern them. Rather, an equal if not larger effort should be afforded to the archaeological interpretation of network science results, or the differences in the interpretative process that a networks perspective implies. I believe none of the scholars that attended the Durham meeting would disagree with that. The studies they presented could be roughly divided into two groups: those that THINK through network and those that DO networks. I believe the former is more important than the latter, because there can be no doing without thinking. Although this sounds like an obvious statement it is worth emphasising it because the use of quantitative network analysis is too often treated like a “black box” approach, which it is not. Every network science study in archaeology, no matter how quantitative, aims to better understand (aspects of) past phenomena. When doing so, the scholar formulates a hypothesis, expresses their assumptions about past relationships and their roles, or at least clearly defines what they mean by the network concepts they use. Only after this phase of network thinking can a scholar proceed to network doing, which involves representing hypotheses/assumptions/the archaeological record as network data (points and lines, and what they mean). The ability to use advanced quantitative tools should not be an excuse for the post-hoc imposition of a theoretical framework that fits the results nicely; nor should the appeal of using fashionable network concepts lead to reluctance to formally express what is meant by them and to evaluate their implications for understanding past phenomena.

Even though none of the three key questions about the role of the networks perspective in archaeology can be conclusively answered at this time, I felt that its future is nevertheless bright. The diversity of possible approaches and perspectives is encouraging and will lead to critical research that promises to help archaeologists better evaluate what approach is useful for their studies of past connectivity, and what is not. Some of these approaches might require multi-disciplinary collaboration, especially the more scary and maths-heavy techniques in the network science toolbox. But archaeologists should never be tempted to outsource the network thinking part of the process. Critical knowledge of the archaeological literature and data leads to an awareness of the relevant research questions, and the same knowledge will lead to valuable interpretations of analytical results and research processes. There might be a thousand pasts out there, and there might be a thousand ways of reaching them, but this quest will always need to be undertaken by archaeologists.

Selected relevant publications:
Brandes, U., Robins, G., McCranie, A., & Wasserman, S. 2013. What is network science? Network Science 1(01): p.1–15.
Brughmans, T. 2013.Thinking through networks: A Review of Formal Network Methods in Archaeology. Journal of Archaeological Method and Theory.
Knappett, C. 2011. An archaeology of interaction. Network perspectives on material culture and society. Oxford – New York: Oxford University Press.

Hurray for workshops!

methodsThe last few weeks of my professional life were nice and hectic, wouldn’t want it any other way of course. There were a lot of events that kept me and my friends quite busy and happy. Here is a short personal review of a few of these: Mathematics of Networks and The Connected Past workshop.

On Monday 16 September there was the Mathematics of Networks meeting in Southampton. This was another one of those excellent multi-disciplinary events that are so popular these days. You obviously don’t hear me complaining, I love these things. But however multi-disciplinary the event, there is always a stronger emphasis on one discipline and you never quite know which one it’s going to be. So in this case it was probably maths/stats. I very much felt like the token humanist offering some light entertainment after lunch. But the questions I and other social scientists got as well as all discussions made it clear that the audience was very much prepared to think about each others problems and provide answers from their respective experiences. What always surprises me is the ability of the more mathsy people among us to come up with algorithms to solve a humanities problem during pub discussions. Love that stuff! I was particularly interested to find out about Jake Shemming and Keith Briggs’ work on Anglo-Saxon communication networks and visibility networks. All slides can be found online.

The pub session of the Mathematics of Networks meeting quickly turned into a promising start for The Connected Past Workshop. Quite a few of the delegates and tutors managed to arrive the evening of the 16th for drinks and dinner, from about ten countries in fact, some as far away as the USA, Canada and Australia. That made me feel a bit nervous, I was really hoping everyone would get out of the workshop what they were expecting. Or even better, some new ideas or research directions they never thought of. As the two days of the workshop passed everything seemed to go smoothly (except for those tiny logistical mistakes that are totally useless but tend to dominate my mind). We had some great discussions, all the delegates and tutors were really switched on, knowledgeable and contributed from their own experiences. What we ended up with (and that was only partly planned) was a set of honest statements by scholars giving their own perspectives on network science in archaeology and history, guiding us through the decisions they made, and sharing their many mistakes and revelations with us. Sometimes it felt very much like being in an Overly Honest Methods meme! Which is great because every academic knows these things actually happen. The best we can do is be aware of them and be honest. And hopefully something useful will emerge at the other end. Many delegates were surprised that we did not sell Network Science as the new hot things to answer all our research questions. Rather the message seemed to be “if it offers the best approach to your research questions then use it, if not then ditch it”. And of course that is exactly how I see network science being useful in our disciplines. We need to be able to understand what it can do for us and evaluate whether it’s the tool we are looking for. No network science in archaeology just for the sake of it, it’s no science if it doesn’t offer anything unique. We decided we will do this workshop again, modified slightly thanks to all the feedback we got. See keep an eye out for future announcements!

On organising the Hestia2 seminar in Southampton

John Goodwin presenting at Hestia2 in Southampton
John Goodwin presenting at Hestia2 in Southampton

As the organiser of the Hestia2 seminar in Southampton I could write about our initial struggle to find a good format, my fight with the university to book a seminar room in a completely booked out campus, discussions with our financial support staff to figure out a balanced budget, the technical flaws with our livestream feed, and of course the many very human feelings like “no-one will turn up!?!” and “what shirt should I wear?”. But none of that would be very interesting to read, and all of these concerns are now firmly pushed to the back of my mind and replaced by the feeling that this seminar was a success!

It will not come as a surprise that the organiser thinks his own event was a success. So let me at least try to come up with some objective-sounding arguments why this was in fact the case.

Multi-disciplinarity: organising a multi-disciplinary event is always risky. You need to address a very diverse target audience and convince them that the topics covered and the discussions will be of interest. People with different backgrounds also tend to talk in different languages: physicists will talk “maths”, classicists will talk “Greek/Roman”, archaeologists will talk “stuff”. The Hestia2 seminar was such a multi-disciplinary event. It was attended by classicists, historians, archaeologists, physicists and designers from the academic, commercial and governmental sectors. Despite this diversity the discussions very often converged into common interests. These included how large datasets like those held by the Ordnance Survey and the Historic Environment Records (HERs) could be usefully combined using new technologies, or how uncertainty about data can be formally expressed and visualised. Finding such common grounds was very much thanks to the chairs of our session. For example, Max Schich confronted the multi-disciplinary background of our audience directly when he asked to what extent individuals need to have skills and knowledge traditionally associated with different disciplines and professions to allow them to apply linked data and network techniques critically and usefully. This question drew very diverse reactions from the audience. Some felt that our educational system should allow for complete diversity and customisations of skills and knowledge, others (and I am part of this particular camp) believe that collaboration is the key, that field specialists should remain specialists but be able to collaborate with specialists in other fields by having some very basic understanding of the other’s “language”, approaches and questions.

Exploration: Hestia2 is not about showing off a great piece of work our team did a few years ago. It’s about learning from different projects’, institutions’ and individuals’ experiences with using innovative technologies to understanding conceptions of space. It’s about exploring the potential of such techniques for providing innovative insights into old datasets, or for allowing us to ask new questions of our data. The Southampton seminar definitely had that exploratory vibe. Very different techniques and projects were presented. The first three talks very much set the scene by giving an overview of different approaches. Max Schich introduced us to networks, Alex Godden provided an insight into the issues surrounding the aggregation and management of historical/archaeological data, and John Goodwin showed how the Ordnance Survey (OS) is implementing linked data. The discussions that followed showed a genuine interest in innovative approaches but also a constant concern with getting at the fundamental issues that keep all this innovation together. For example, in our discussion we never restricted ourselves to asking how something could be done, but always focused on why we should do it in the first place. The question of why HER data could not be seamlessly linked with OS data, for example, was not because of technological restrictions but concerns about protecting cultural heritage and also commercial concerns. Once such concerns were addressed we turned our attention to how combining such diverse datasets could allow us to ask new research questions, or could lead to a better management of historical resources.

Weather: it has sunny and hot. That makes every event an instant success!

I am very much looking forward to the second Hestia2 seminar in Stanford, where I will be able to put my feet up a little and enjoy another round of stimulating multi-disciplinary exploration.

Review of Malkin’s A Small Greek World published

9780199734818_450The end of 2011 for me was marked by the publication of two new networky books. The first one was Knappett’s An Archaeology of Interaction, which I reviewed for Antiquity (and I wrote a more in-depth review on this blog). The second one was Irad Malkin’s A Small Greek World, my review of which finally appeared in the journal Classical Review. You can access it on the journal’s website, download it from my bibliography page or read it here.

IRAD MALKIN. A small Greek world. Networks in the ancient Mediterranean. xix+251 pages, 18 illustrations. 2011. Oxford: Oxford University Press; 978-0-19-973481-8 hardback $60.

History books too often read like a series of unconnected events, dates, places and people, the sum of which is considered the historical narrative. In ‘A Small Greek World’ Irad Malkin does the exact opposite by focusing on the ties that bind and give meaning to historically attested entities. The reader is taken on a guided tour through the web of countless historical relationships between people, places and cultural practices in the Archaic Mediterranean and Black Sea. One is invited to explore this “Greek Wide Web” as a set of nodes and links to appreciate its small-world network structure and how long-distance links were instrumental to the emergence of “Greek civilization as we know it” (p. 5). At least, this is the hypothesis Malkin advocates in his latest book.

The introductory chapter sets out Malkin’s network perspective, which forms the book’s main innovative contribution to the study of ancient history (mainly due to an adoption of concepts from physics), which is why this review will be largely concerned with evaluating this aspect of the book. Malkin adopted the concept of small-world networks from two physicists, Duncan Watts and Steven Strogatz, who use the term to refer to a range of networks with a high degree of local clustering and a low average shortest path length. This means that although nodes are largely only connected to nodes within their cluster, every so often a link appears that bridges the gap between clusters and facilitates the flow of material or immaterial resources between clusters. Malkin was also influenced by two other physicists, Albert-László Barabási and Réka Albert, who coined the term scale-free networks for networks that exhibit a power-law distribution in the number of their nodes’ links. For the creation of this type of network structure, Barabási and Albert suggested a process of preferential attachment in which nodes are continually added to the network and preferentially create links with nodes that are already well connected, thus giving rise to super-connected hubs. In this book Malkin argues that during the Archaic period people and places around the Mediterranean and Black Sea were connected in a way that resembled a small-world structure, driven by processes of preferential attachment. Malkin stresses throughout the book that it was the long-distance links and decentralization of the small Greek world that facilitated the emergence of what he calls Greek civilization.

These network ideas are not expressed and validated in a quantitative manner, however, since historians of antiquity are considered not to possess enough data to identify such patterns and processes with any statistical significance (pp. 19, 25). Instead, Malkin takes a qualitative approach by adopting the vocabulary of network science, and the key features of small-world and scale-free network models in particular, and applies it to a series of historical examples in chapters two to six. Regardless of this, Malkin does consider his qualitative network perspective more than a mere description of the historical Greek network and stresses the explanatory value of his approach. The aims of the book are therefore twofold: to point out networks and processes of network formation through numerous examples, and the interpretation of the implications of describing structures and processes using a formal network vocabulary.

Chapters two and three illustrate reverse processes of the emergence of identity (as identified by Malkin through abstract as well as concrete historical examples) through networks. In chapter two the Rhodians’ dispersal overseas is seen as the reason for the consolidation of the island identity of Rhodes. Chapter three turns this process on its head by arguing for the emergence of the Sikeliôtai identity of Greeks from all over converging in Sicily. The altar of Apollo Archêgetês, only accessible to the Greek residents of Sicily, is considered the earliest expression of this ‘Greeks away from home’ identity. Chapter four brings Herakles the Greek and Melqart the Phoenician to the stage as examples of the existence of mythical and cultic networks, facilitating coexistence and peaceful mediation as well as justifying antagonism between ethnic groups. Malkin continues his series of example networks by focusing on the Phokaian network in the western Mediterranean in chapters five and six. Most interestingly, the evolution of this network is seen as changing from a many-to-many structure to one consisting of local clusters dominated by hubs with long-distance links, giving the example of Massalia and the coastal zone in southern France (described as a middle ground). In chapter six Malkin explores the similarities in cults (Artemis of Ephesos) and institutions (nomima) of the Phokaian network, which are considered to express the Phokaian’s self-perception. The concluding chapter rephrases many of the examples into a rich description of Malkin’s small Greek world hypothesis, which shows strong similarities to his previous work on the emergence of Greek identity but now seen from a network standpoint.

The sheer number of examples and the detail to which they are described makes the book’s narrative difficult to follow in places. Indeed, for most chapters the approach taken and crux of the argument are not clearly stated in the introduction and conclusions. At times this leads one to loose track of the bigger picture and the general aim of the book. The figures are of high quality although they are limited (with the exception of chapter one) to maps indicating the places mentioned in the text.

The descriptive first aim of the book is definitely achieved, through the identification of historical links, networks and problems that are better served by a networks approach. The second aim of interpreting the implications of the network perspective is very thorough as far as the description of the small world hypothesis is concerned. In this reviewer’s opinion, however, it does seem underrepresented in one important respect: the absence of convincing argumentation why the emergent property that is “Greek civilization” could not have emerged on a “Greek Wide Web” with a structure other than the hypothetically identified small-world. Malkin’s discussion of the alternative network structures advocated by Braudel (pp. 42-44), Horden and Purcell (pp. 44-45), and Jean-Paul Morel (p. 153) does not give the impression that the likeliness of his hypothesis is any greater. On the other hand, Malkin rightly argues that dynamic network processes add explanatory power to these structures, and he illustrates this throughout the book for his own hypothesis. Malkin seems to be very aware of this issue when stressing that “The identification of connections and particular networks falls within the historian’s search for ‘what was there’ (the factual, or the truth level); the suggestion that network dynamics forms the Greek ‘small world’ is by contrast an interpretation, but to my mind it is one that has a high probability of being right” (p. 207). Yet the book too often reads like a summing up of historically attested ties in a one-to-one relationship with complex network concepts that are by no means exclusive to small-worlds (e.g. emergence, self-organization, hubs, fractal patterning, preferential attachment, decentralization, multi-directionality, phase transitions, clustering) to allow for disregarding alternative network structures out of hand. The innovative network perspective is also only to a limited degree utilised to revisit concepts like ethnicity, Greek civilization, and identity. It is a new hypothesis that focuses largely on explaining past processes of emergence from given states.

Malkin, therefore, piles up evidence for his hypothesis to create the fascinating concept of the small Greek world, which will no doubt prove a rich and useful perspective for future research. However, he does not increase its credibility through falsifying other possible structural incarnations of this network approach. ‘A Small Greek World’ illustrates the potential of a network perspective for understanding the emergence of Greek culture and identities (concepts that themselves are by no means less ambiguous than the ‘small Greek world’ hypothesis), but it is really only a starting point that requires further formalisation and explicit confrontation with the implications of alternative hypothetical network structures.

CAA2011 networks session summary and discussion

The networks session at CAA2011 in Beijing was a success! We had some great papers and a fascinating discussion. Read the summaries of the papers, the questions and answers, as well as the discussion here. Read more about the session, including the abstracts and the introduction on the dedicated page.

The first presentation of the day was by Maximilian Schich and Michele Coscia talking about ‘Untangling the Complex Overlap of Subject Themes in Classical Archaeology’.

Maximilian and Michele used the Archäologische Bibliographie, a library database consisting of over 450.000 titles, 45.000 classifications, and 670.000 classification links. They looked at the co-occurrence of classifications, creating networks where two classifications are connected if they appear in the same book as well as networks where classifications are connected when the same author writes about them. Using whatever database software you can look at the local level of this massive dataset. This was not of interest to the authors. In stead, Max and Michele looked at the bigger picture. They devised a method that allowed them to explore the dataset on three different scales: the local level (database level), the meso-level and the global level. On the global level they were able to identify academic communities, but also clusters of communities (so communities of communities). They also looked in detail at how these communities evolved over time. On the meso-level they threshold the data based on co-occurrence and significance, which produced interesting results. Max and Michele concluded that this approach to academic literature allows us to look at the fine-grained structure of how archaeology actually works. Their three-level method using hierarchical link clustering and association rule mining made it blatantly clear that complex overlaps are everywhere in academia!

Questions: Guus Lange asked what type of clustering was applied, to which Max responded that no clustering was performed on nodes but on the links. Graeme Earl asked how the classifications were derived from the database and whether they thaught about exploring how the classifications themselves grew and transformed. Max replied that there is no limit to the number of books per classification but there is a sharp limit to the number of classifications there are per book. What is interesting, he said, is that we nevertheless get this big picture. Tom Brughmans wrapped up with a final question about how long it took them to do this work. Michele and Max mentioned that it took them one year but once the workflow is engineered it could be done in two weeks time.

Diego Jimenez was our next speaker. He presented on ‘Relative Neighborhood Networks for Archaeological Analysis’.

Diego is interested in archaeological attempts to find meaningful spatial structure between archaeological point data. He relies on graph theory to find structure based purely on the spatial distribution of points and suggests objective ways of analysing connections between them. In his talk Diego focused mainly on the methodology rather than any specific applications. Rather than nearest neighbour approaches, he suggested a relative neighbourhood concept as the basis for his method. Two points are relative neighbours if the regions of influence drawn around this pair does not include other points. Graphs can be constructed using this concept. Most interestingly, Diego mentioned that a parameter beta can be included to change the regions of influence. This allows for a series of graphs to be created with different levels of connectivity. Diego suggested some space syntax approaches to analysing these graphs including graph symmetry, relative asymmetry and distributedness.

Questions: Maximilian Schich was interested in how control was defined in Diego’s analysis of the graphs and mentioned that peripheral nodes might often have a high level of control in a network. Diego mentioned that these are indeed important patterns that need to be acknowledged by archaeologists and his method would be a way to be sensitive to them.

After Diego we had the honour of listening to a historians experiences with network analysis. Johannes Preiser-Kapeller talked about ‘Networks of border zones – multiplex relations of power, religion and economy in South-eastern Europe, 1250-1453 CE’.

Johannes’ paper made it very clear that, although archaeologists can rarely obtain datasets of such quantity or quality as in other disciplines, we still have sources that inform us of different types of relationships for which a networks approach can lead to highly interesting results. He constructed five distinct networks from different data types (streets, coastal sea routes, church administration, state administration, participants of the 1380 synod) some of which were compared for three different moments in time (1210, 1324, 1380). Initially some general measurements, like average distance, clustering coefficient and density, are used to explore the topology of individual networks, as well as compare between networks of different sources. Secondly the overlap of groups of related nodes is identified to explore the correlation between different networks. Johannes then merged all these networks to create what he considers a multiplex representation of frameworks of past human interactions. Thirdly, the combined effects of the multiplex network on the topology of social interaction, as illustrated through the participants in the 1380 synod, is explored. He concluded by stating that this framework that emerged from different sources might be more than merely the sum of its parts. In short, even though we are dealing with fragmentary and limited datasets, applying a networks perspective explicitly might still guide us to highly interesting and surprising results.

Mihailo Popovic presented the final paper before lunch. His talk titled ‘Networks of border zones – a case study on the historical region of Macedonia in the 14th century AD’ was strongly related to that of his colleague and fellow historian Johannes.

Mihailo’s paper explored the border zone between the Byzantine empire and the emerging Serbian state in the 14th century AD. His case-study focused on the area of the city Stip and the valley of the river Strumica. Four central places were identified in the valley on the basis of written medieval sources: the towns of Stip, Konce, Strumica, and Melnik. Mihailo is interested in understanding how these places interact with each other. For example, can an exclusive relationship between the central places and the surrounding smaller settlements be assumed? Or did all settlements interact equally with each other? Mihailo stresses the importance of evaluating the landscape on the ground to explore how this might have influences urban interactions. Based on Medieval written sources that identify the larger settlements as religious, administrative and economic centres, he argues for an exclusive relationship of the larger towns with the smaller ones. This leads to astral-shaped networks. Mihailo’s analysis shows that Strumica has the highest closeness centrality value, whilst Stip has the highest betweenness value. To conclude he stressed the wider questions that his networks approach leave open: is the settlement pattern complete? Is the network realistic in view of the landscape? Is the networks’ astral-shape justifiable or did the villages also interact with each other? May we assume interactions between other villages? How to integrate human behaviour?

We reconvened in the afternoon to listen to Ladislav Smejda talking about ‘Of graphs and graves: towards a critical approach’

Ladislav discussed the artefact distributions from a cemetery dated around 200 BC. He explored eleven attributes consisting of grave dimensions and the presence or absence of grave good categories, which can appear in many combinations. Ladislav limited the relationships of co-presence of grave goods to statistically significant correlations, which resulted in a graph representing his eleven attributes and relationships of positive and negative correlations between them. He then moved on to divide the graph into two substructures. Substructure A is defined by correlations between ornaments (faience beads, bone beads, hair ornaments) and grave depth. Substructure B includes stone artifacts, cattle ribs and grave length. These two sets seem to show strongly different patterns, which can be explored as networks. Simple networks were created based on the presence or absence of artefacts significant to either substructure A or B, showing different structured. Secondly, Ladislav introduced the concept of the hypergraph where the edges are more like areas in which more than one node can be included. Ladislav concludes that a graph theory and network analysis approach is useful to handle, visualise, and explore the structure of archaeological datasets, whilst leaving plenty of options open to take the analysis further with different tools (like GIS).

Questions: Ladislav’s presentation sparked many questions, partly because we had plenty of time in the afternoon due to serious changes in the conference schedule. So I decided to transcribe the questions as a simple dialogue.

Leif Isaksen: what does the negative correlation mean? That the attributes don’t occur together?

Ladislav: they don’t appear together with statistical significance.

Maximilian Schich: what’s the negative correlation with grave depth and faience beads?

Ladislav: deep graves have bone beads and shallow graves tend to have faience beads.

Leif Isaksen: how has the grave depth been recorded?

Ladislav: data was taken from excavation reports. There is no specification of how they measured that. The whole site was excavated by a single person. Possibly grave depth was measured from the top soil downwards.

Maximilian Schich: You could compare every link in this diagram, maybe as an XY diagram where you have bone beads vs grave depth for example. Do you know how many bone beads there are? How many graves? Are these measured just as presence/absence or as real counts?

Ladislav: There are 70 graves with bone beads, and 470 graves in total. I tried both approaches but presence/absence is better because in many cases it was impossible to count precise numbers. I don’t think it is important to know how many bone beads they had exactly.

Maximilian Schich: so you could draw an XY diagram. If you only have 470 graves it’s very easy to draw a histogram. And instead of the correlation you could give us all the data points.

Ladislav: I did all these things. At the moment I have so many outputs of this data that it could not be presented in a 15 minute paper. Clearly there is much more you could with this data.

Maximilian Schich: how can you assign grave depth to a region where there is no grave?

Ladislav: the grey background is just an interpolation of the grave points. The crucial thing this shows is that there are no deep graves on one end of the matrix and no shallow graves on the other.

Diego Jimenez: is there any significance in the distribution of objects within each grave, and is that relevant for the analysis.

Ladislav: it’s recorded, I tried to follow this up but not with graph theory.

Diego Jimenez: this is what sparked my interest in using graphs, as I used it to understand the spatial distribution of artefacts within graves. The spatial arrangement might have a symbolical importance.

Tom Brughmans: it’s a good example of a network within a network as well.

Leif Isaksen: it would be great to see these graves’ locations projected in geographical space, did you pursue a geographical approach as well?

Ladislav: yes, but that is the topic of another presentation.

Tom Brughmans: I am not sure if the statistics used to explore correlations are necessary, because these correlations might just emerge when exploring the co-presence of different types of artefacts as a network.

Ladislav: the presence/absence is exactly what is represented, so it is a different way of achieving the same thing.

Maximilian Schich: you have enough data but not too much to prevent a real networks visualisation. There is no need to reduce your data to a few nodes and links. All your data can be shown on one graph and a few histograms.

Ladislav: I did not do this because I am looking for the simplest possible structure, in the simplest possible representation.

Due to the changes in the conference schedule the afternoon also saw two unscheduled presentations by Leif Isaksen and myself being added to the network analysis session.

Tom Brughmans presented a paper titled ‘Facebooking the Past: a critical social network analysis approach for archaeology’.

I started out with a short fiction about how Cicero became consul of Rome thanks to Facebook and Twitter. Obviously, that is not the story we will find in the history books. But by making the analogy between modern ideas of social networks and past social processes it becomes clear what it is we are actually doing when using social network analysis. I argued that there are three issues related to the archaeological (and indeed historical) use of social network analysis. Firstly, that the full complexity of past social interactions is not reflected in the archaeological record, and social network analysis does not succeed in representing this complexity. Secondly, that the use of social network analysis as an explanatory tool is limited and it implies the danger that the network as a social phenomenon and as an analytical tool are confused. Thirdly, human actions are based on local knowledge of social networks, which makes the task of deriving entire past social networks from particular material remains problematic. To confront these issues I argued to turn the network from the form of analysis to the focus of analysis and back again in an integrated analytical process drawing upon ego-networks, complex real-world network models and affiliation networks approaches.

Discussion: the questions about this paper changed into a fascinating discussion about the nature of archaeological and historical data and how this influence our use of network techniques.

Maximilian Schich: I think that indeed data from today is different than from the past but only because more is different. In a sense I think it cannot be justified to say that we should not look for social networks because the data is incomplete. Modern day data, like mobile phone record for example, are also incomplete. Facebook does not cover all social interactions. One topic that has been mentioned a lot today is that of multiplex networks. There is a conceptual danger with this because it assumes that we can discretize between different types of networks, whilst actually that is not possible. When collecting data there is one thing that is definitely different from data like mobile phone networks for example, which is the multiplicity of opinion. If you collect something and I collect something the data will look completely different. All these things are complicated, a lot of time needs to be invested in this, I agree that we have to work with what we have. But we should not capitulate in front of this problem saying that it’s perfectly fine to just bullshit theoretically because the data is unavailable.

Tom Brughmans: I agree that archaeological data is not necessarily any different than data sociologists or physicists use, like mobile networks for example. Another example is e-mail communication. A sample of this type of social interaction might be limited because some people were out of office whilst you were taking the sample, and it is also an indirect reflection of social relationships as we explore the e-mail directly but not the people. So our data might not be different. But what possibly makes archaeology (and other historical disciplines) different is that all our theory is geared towards this issue. We are very aware that we are dealing with indirect fragmentary samples to explore dynamic processes in the past. Whilst in other disciplines scholars might over simplify this issue, in the historical disciplines we are very aware of it and cannot avoid it. Another difference might be what you said that when different people excavate the same thing, different data will emerge. But more crucial I think is that after collection the data is actually destroyed, it is not a repeatable test. The data only lives on in a structure that makes sense to the person who collected it. So given these two issues I think archaeological applications of social network analysis can be different from other disciplines.

Yasuhisa Kondo: Just a comment. I believe that social networking like Facebook and Twitter is also changing archaeologists’ behaviour. When I was in Oman a few months ago, for example, the Middle East crisis was picking up and I was informed about the situation of Egyptian heritage through social networks. Secondly, in Japan we use Facebook to collect data. So it is interesting to see that it is not only useful to think about present social relationships between archaeologists but also about past social networks.

Johannes Preiser-Kapeller: when comparing modern complex network analysis in physics and historical network analysis, in physics scholars don’t want to just analyse but they also want to explain, to understand the mechanism that makes the network function. They generate ideas on how such network actually worked, like through preferential attachment for example. We do not know if networks in the past actually worked in the same way, if such mechanisms can be imposed on historical networks. Our data sometimes isn’t even large enough to identify degree distributions that reveal power laws for example.

Tom Brughmans: I am glad that you bring this up because I have been struggling with a similar issue. Do these real-world network emergent properties actually explain anything. Aren’t they just a description of a complex network structure, of how it evolves rather than explain the network. The descriptive aspects of such models can easily be applied to historical data, when we accept the assumption that the whole is greater than the sum of its parts and complexity arises from local interactions. But it does not really explain much does it.
Johannes Preiser-Kapeller: modern complex network models assume that they are not merely descriptive but they are laws that explain how things like social relationships functioned. It’s more than description, they are looking for mechanisms. The question is if we can also identify such mechanisms for past networks which can help us to explain how social interaction worked.

Maximilian Schich: concerning the power-law thing, preferential attachment is only one of thousands of mechanisms which can result in a power law. And in some cases it can not even be proven that the power law is there because of a lack of data. So we cannot blame the people that came up with the idea of preferential attachment in the first place as if they assumed that it explained all power laws. It is not their fault that they got cited 60.000 times. We should acknowledge that this is just one model that actually works, and it explains a lot, just like the small-world model. But both of them are incomplete. Concerning historical networks: I think it is a big mistake of historians or other scholars in humanities to think that we are special, cause we are actually not. Of course we have different documentation and different numbers. But the underlying approach of hypothesis testing and of saying “let’s look at what structure the data has”, that is the approach complex network scientists have. They do not assume a universal law. This is the same approach taken in the humanities.

Mihailo Popovic: many people are not aware of the exact historical situation. Like 14th centure Byzanthium for example: 90% of the population lived in vilages, the flow of information does not exist on an international level it is a local thing.

Maximilian Schich: are you sure?

Mihailo Popovic: I am sure, based on the sources we have. Thirdly, there are slaves in the villages who’s movement is restricted. Finally, Illiteracy is immense. To come to my point: we have written sources that are written by 5% of the population, if even that. And of those perhaps 20% percent survive. So what do we do? We cannot just assume that comparing a dataset of six million people communicating over the internet with a historical dataset like the one I described can be done through the same approach. We have to face the reality of the historical period. It took us a lot of time and effort to collect these relatively small and still fragmentary datasets.

Maximilian Schich: but we can agree that things are being spread between people, even if they are not aware of it. Information can spread in the same way electricity spreads for example, electrons push other electrons along, not every electron goes all the way from Europe to China. We have such a situation where we can assume that some information was spread for most periods in the past. So to say that there are individuals who are immobile and construct sampling boundaries based on that, I don’t think such a strict limitation can work.

Johannes Preiser-Kapeller: of course, there was some kind of globalization already in the 14th century, there was some connection which even reached villages. It would be perfect if we could paint a picture of such a global system. We can do it on a superficial level, but we do not have the necessary sources to go in more depth. A prosopographic database of the Byzantine period, for example, contains 30.000 people. Of those, 80% were clerics and not more than 200 were farmers. We can see what is going on for the top 5% of the people, and we can see the mechanisms like preferential attachment working on this level. But we are still struggling with the artificial border created by our data, as you mentioned. We do not have the entire system. This sample problem will always be there in the historical discipline.

Maximilian Schich: that’s exactly the same problem as we have in any other discipline. It is not a history or non-history problem but a percolation problem. Physicists working on percolation have to come up with a solution and then we can make an educated gues of how much of the system we have.

Johannes Preiser-Kapeller: let me give you another example. When I showed my work to Stephan Thurner in Vienna, who worked on a massive dataset of 300.000 individuals interacting through a computer game, he said my dataset of only 200 aristocrats is not enough. If you do not have at least 1000 individuals you cannot identify any mechanism, you need statistical significance. So this is a limit imposed on historical disciplines in applying interesting mechanisms identified in complex real-world networks.

After the discussion we still had the pleasure to listen to Leif Isaksen talking about ‘Lines, Damned Lines and Statistics: Unearthing Structure in Ptolemy’s Geographia’. Sadly my tape recorder died at this point, so here is Leif’s abstract rather than a review.

Ever since the rediscovery of Ptolemy’s Geographia in 1295, scholars have noted that it is troublingly inconsistent both internally and with the environment in which it was supposedly compiled. The problem for analysts to overcome is that the catalogue has been corrupted, amended and embellished throughout its history. It is therefore imperative to find more robust means to look for structural trends. Recent publications of the theoretical chapters and a digital catalogue of coordinates provide a variety of new possibilities. We are not alone in advocating computational procedures but will discuss two techniques that do not appear to have been considered in the literature so far and the conclusions they appear to give rise to.

First, statistical analysis of the coordinates assigned to localities demonstrates clearly that ostensible precision (whether to the nearest 1/12, 1/6, 1/4, 1/3 or 1/2 degree) varies considerably by region and feature type and is locally heterogeneous. In other words, the composite nature of the data cannot only be confirmed, but we can build a clearer picture of how the sources varied by area. Secondly, while many studies have addressed either the point data or the finished maps, simple linear interpolation between coordinates following the catalogue provides a unique insight into the ‘invisible hand’ of the author(s). The unmistakable stylistic families that emerge, and the occasionally arbitrary limits imposed on them, provide further important evidence about the catalogue’s internal structure.

‘Connecting the dots’ on Electric Archaeologist

On his Electric Archaeologist blog Shawn Graham just wrote a very kind comment on my recently published article titled ‘Connecting the dots: towards archaeological network analysis’ published in Oxford Journal of Archaeology Volume 29, Issue 3, pages 277–303, August 2010.

Shawn writes: “It is well worth a read. He provides a corrective to my own focus on networks as social networks, pointing out quite rightly that there’s more to it than that” and “Tom’s article has given me much food for thought… “.

You can download the full paper (pre-published version) from my bibliography page.

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