Medieval social networks 2: charters and connections

As a follow-up to my first post on social network analysis, I’m now gradually reading some of the many books and articles on historians’ use of network analysis that readers of my blog suggested. And having read a couple of chapters of Giovanni Ruffini, Social Networks in Byzantine Egypt, I’m coming to realise that one of the most difficult issues for those of us working with documentary sources is deciding what counts as a connection between two people and what links should therefore be included in the network.

The majority of the late antique/medieval network analysis studies that I’ve looked at work by hand-crafting links. Someone sits down, works their way through their sources and picks out by eye every link between two people (or two places). Often, they also categorise the link. For example, Elizabeth Clark, when studying conflicts between Jerome and Rufinus, divided links into seven different types: “marriage/kinship; religious mentorship; hospitality; travelling companionship; financial patronage, money, and gifts; literature written to, for, or against members of the network; and carriers of literature and information correspondence.”

(Elizabeth A. Clark, “Elite networks and heresy accusations: towards a social description of the Origenist controversy”, Semeia (56) 1991, 79-117 at p. 95).

Similarly, Judith Bennett did the same thing when looking at connections of families recorded in the Brigstock manorial court records:

The content of these transactions has been divided into six qualitative categories that collectively encompass all possible transactions. These categories are based upon whether the network subject interacted with an-other person by whether the network subject interacted with an-other person by (i) receiving assistance, (2) giving assistance, (3) acting jointly, (4) receiving land, (5) giving land, or (6) engaging in a dispute.

(Judith M. Bennett, “The tie that binds: peasant marriages and families in late medieval England”, Journal of Interdisciplinary History 15 (1984), 111-129, at p. 115).

And for networks of places, Johannes Preiser-Kapeller, “Networks of border zones: multiplex relations of power, religion and economy in South-Eastern Europe, 1250-1453 AD”, in Revive the past: proceeding of the 39th conference on computer applications and quantitative methods in archaeology, Beijing, 12-16 April 2011 edited by Mingquan Zhou, Iza Romanowska, Zhongke Wu, Pengfei Xu and Philip Verhagen,. (Amsterdam, Pallas Publications, 2012), 381-393, combined existing geographical datasets on late antique land and sea routes with details of church and state administrative networks he’s compiled from documentary sources.

Such approaches create very reliable networks, but they’re hard to scale up. Clark looks at 26 people; Judith Bennett has 31 people and 1,965 appearances in extant records from 1287-1348. Preiser-Kapeller has around 270 nodes and 680 links in total. Rosé’s study of Odo of Cluny, which I discussed in the previous post, had 860 links. For charters, such hand-crafted networks would probably only allow the exploration of small archives or individual villages.

What is more, researchers often want to carry out social network analysis as an offshoot of more general prosopographical work, such as creating a charter database. But it’s hard to analyse links until you’ve first created a prosopography, because it’s only when you’ve been through all the charters that you have a decent idea of whether two people of the same name are actually the same person. (There’s a further issue here about whether you may end up with circular reasoning between prosopography and network analysis, but I’ll leave that for now). So in theory, you’d need to go through all the charters first to identify people and then have to go back to assess whether or not they are linked in a meaningful way, doubling your work.

As a result, some researchers have started trying to see if there are ways of automatically creating networks from existing databases or files, developing methods for analysing charters that (in theory) can be scaled up relatively easily. In the rest of the post I want to look at the relatively few projects I’m aware of attempting to do this and outline how we might approach the problem with the Making of Charlemagne’s Europe dataset.

The three projects I’m looking at are by Giovanni Ruffini, working on the village of Aphrodito in Egypt (see reference above), Joan Vilaseca, who’s been experimenting on creating graphs from the early medieval sources he’s collected at and a controversial article by Romain Boulet, Bertrand Jouve, Fabrice Rossi, and Nathalie Villa, “Batch kernel SOM and related Laplacian methods for social network analysis”, Neurocomputing 71 (2008), 1257-1273.

Ruffini is explicit about how he’s creating his networks and the problems that may result from this (pp. 29-31). He’s taking documents and creating “affiliation networks”: all those who appear in the same document are regarded as connected to one another. As he points out, the immediate problem is that this method can introduce distortions if you have one or two documents with very large numbers of names. For example, one of the texts in his corpus is part of the Aphrodito fiscal register and has 455 names in it, while the average text names only eleven (p. 203). If such a disproportionately large text is included, analysis of connectivity is badly distorted, with all the people appearing in the fiscal register appearing at the top of connectivity lists.

The same effect can be seen in Joan Vilaseca’s graphs. If you look at his first attempts at graphing documents from Catalonia between 898-914, they’re dominated by the famous judgement of Valfogona in 913.

But Joan’s graphs also show an additional problem. His first graphs also give great prominence to Charles the Simple and Louis the Stammerer, because they appear so often in dating clauses. When he starts looking for measures of centrality in his next post he initially finds the most connected people to be St Peter, the Virgin Mary and Judas Iscariot (who appear frequently in sanction clauses).

This brings us to the key question: what does it mean to be in the same charter as another person? The problem is that people are named in charters for so many different reasons: they may be saints, donors, witnesses, relatives to be commemorated, scribes or even the count whose pagus you are in. People may also appear as the objects of transactions: some of our early decisions on the Charlemagne project were deciding how we would treat the unfree (and possibly the free) who were being transferred between one party and another. Such unfree have an obvious connection to the donor and the recipient. But do they have any meaningful relationship to the witnesses or the scribe? At least with witnesses, there’s a reasonable chance in most cases that they all physically met at some point, but I don’t know of any evidence that the unfree would necessarily have been present when their ownership was transferred by a charter.

So simple affiliation networks, even when you eliminate disproportionately large documents and people mentioned only in dating or sanction clauses, can still be inaccurate representations of actual relationships. One possible response to this problem is to include as links only types of relationships that are themselves spelled out in the charters. Joan has some graphs showing only family and neighbourhood relationships, for example. Ruffini (p. 21) suggests the possibility of using data-sets where a link is defined as existing only when there is a clear connection between two parties in a document e.g. between a lessor and a lessee. But as he points out, we would then have much smaller data-sets. And for early medieval charters, in particular, focusing on the main parties to a transaction only would simply demonstrate that most transaction were about people donating or selling land to churches and monasteries, which is not exactly new information.

Are there any other ways to cut out “irrelevant” connections while keeping those we think are likely to show meaning? Another approach that Joan tries uses affiliation networks, but then removes links where two people occur together in only one document. For his interest in identifying key members of Catalan society, focusing on the most important links may well make sense. But they potentially distort the evidence on one question of wider interest: how significant are weak ties in charter-derived networks? Weak ties, where two people interact only occasionally, may paradoxically be more important for spreading information or practices. Given we have only a small subset of interactions preserved via charter data, significant weak ties may be lost if we start removing data from affiliation networks in this way.

Implicitly, at least, an alternative method for selecting links within what’s broadly an affiliation network is given by Boulet, Jouvet, Rossi and Villa. As they explain in their study of thirteenth and fourteenth century notarial acts, they constructed a graph in the following manner (pp. 1264-1265):

First, nobles and notaries are removed from the analyzed graph because they are named in almost every contracts: they are obvious central individuals in the social relationships and could mask other important tendencies in the organization of the peasant society. Then, two persons are linked together if:

_ they appear in a same contract,
_ they appear in two different contracts which differ from less than 15 years and on which they are related to the same lord or to the same notary.

The three main lords of the area (Calstelnau Ratier II, III and Aymeric de Gourdon) are not taken into account for this last rule because almost all the peasants are related to one of these lords. The links are weighted by the number of contracts satisfying one of the specified conditions.

Though it’s not clear why people are regarded as linked if they use the same notary, the other criteria seem to be ways of trying to filter out distortions that potentially arise from notorial practices. If men are routinely described in terms of their affiliation to a lord e.g. “A the man of B”, then an affiliation network will derive from a sale between “A the man of B” and “C the man of D” not only the justified links A to B, C to D and A to C, but also links that in practice are unlikely to exist or at least are not proven to do so, i.e. A to D, C to B and B to D.

So how might we balance distortions from applying the affiliation network model to charter data against loss of data or an unfeasibly high workload if we don’t use this method? The model for the Making of Charlemagne’s Europe database allows inputting of relationship factoids, which will catch explicit references to people as the relatives or neighbours of others. Graphs using such data will be relatively easy to construct.

We are also, however, recording “agent roles”, used to identify what role a person or an institution plays within an individual charter or transaction (e.g. witness, scribe, object of transaction, granter). At the minimum, any social network analysis application added to the system should probably allow a user to choose which of these roles they want included within the graphs to be created. There should also be some threshold (either chosen by us or user-defined) for excluding documents that contain “too many” different agents. We’re still not going to get the precision graphs that hand-crafting links will give, but we can hopefully still get something that will tell us something useful about how people interact.

Medieval social networks 1: concepts, intellectual networks and tools


Data visualization of Facebook relationships by Kencf0618

Network analysis is one of those areas which keeps on cropping up as a possibility for medieval researchers. (There have been some interesting discussions and examples previously at A Corner of Tenth Century Europe and Cathalaunia, which I’ll discuss more in a later post).

Since one of the hopes of the Making of Charlemagne’s Europe project I’m working for is that the data collected can be used for exploring social networks, I thought it would be useful to find out a bit more about what has been done already. So is this my first attempt to get a feeling for what’s been done with medieval data and what it might be possible to do.

I should note at this point that I’m drawing very heavily on the work of Johannes Preiser-Kapeller, especially his paper: “Visualising Communities: Möglichkeiten der Netzwerkanalyse und der relationalen Soziologie für die Erfassung und Analyse mittelalterlicher Gemeinschaften”. I found out about many of the projects I discuss from this paper, so I am grateful for to him for providing such a primer. My focus is slightly different to his, however, as what I’m particularly interested is the type of research questions that social network analysis might be used to answer, more than the details of particular projects.

Defining networks
One immediate problem in knowing where to look comes because the key mathematical tools and visualization techniques can be applied to very different kinds of data. The underlying concepts come mainly from graph theory. Wikipedia defines that as: “the study of graphs, which are mathematical structures used to model pairwise relations between objects from a certain collection. A “graph” in this context is a collection of “vertices” or “nodes” and a collection of edges that connect pairs of vertices. A graph may be undirected, meaning that there is no distinction between the two vertices associated with each edge, or its edges may be directed from one vertex to another.”

What that means is that you can use the same basic techniques to study anything from a road network via the structure of novels, to how infections spread through a population. But it also means that the type of network and how you can analyse it depends crucially on several factors. These include how you define a node and edge, whether all edges are the same (or whether you’re counting the connections between some pairs as somehow different/more important than others) and whether it’s a directed or undirected graph.
The size of the network is also crucial, and that differs vastly between disciplines: it’s when you see a physicist commenting that “At best power law forms for small networks (and small to me means under a million nodes in this context) give a reasonable description or summary of fat tailed distributions” that you know that not all networks are the same kind of thing. One of the things that interests me when looking at projects is the extent to which data visualization is important in itself or whether the emphasis is on mathematical analysis of the underlying data.

Data quality

There are, inevitably, particular issues with data quality for medieval networks. The obvious one is whether the information you have is typical or whether the reasons for its survival bias our evidence excessively from the start. (The answer is almost certainly yes, but medievalists wouldn’t know how to cope if they had properly representative sources, so let’s move on rapidly).

Another big issue is identifying individual nodes. You can in theory have anything as nodes: an individual, a “family”, a manuscript, a place, a type of archaeological artefact, a gene, a unit of language. (I’m not going to look at either linguistic or genetic network analysis in what follows, but there are projects doing both of those). The problem with medieval data is that there’s almost always some uncertainty about identification: are two people the same or not? What do you do about unidentifiable places? How do you decide whether two people belong to the same family?

Then there’s question of how you define a connection between two nodes. What makes two people connected to one another? The data you extract from the sources obviously depends on decisions made about this, but for a lot of medieval networks there’s the added complication that not all connections are made at the same time. If you have a modern social network where A connects with B and (simultaneously) B connects with C you can make certain deductions about the network from data about whether or not A and C are connected. If you have limited medieval data where A connects with B and 20 years later B connects with C, can you model that as one network, or do you have to take time-slices across the network (which may often reduce your available data set from small to pathetic)?

Varieties of projects
Of the medieval history projects I’ve come across so far (I suspect there’s a whole slew of others in fields such as archaeology), most seem to fall into three categories. There are studies on networks of traders, such as by Mike Burkhardt on the Hanse. There are probably other similar examples: I’ve not yet had a chance to investigate whether the important work by Avner Greif on traders in the Maghreb also uses network analysis or not. But these kinds of studies are unlikely to be relevant to any early medieval project, because they will almost certainly rely on relatively large-scale sets of data from a short chronological range (account-books, registers of traders etc). Such data sets simply don’t exist for the periods I’m interested in.

The other two types of medieval network studies I’ve noticed are ones which are looking at intellectual networks or the spread of ideas (with some possible overlap with spread of objects more generally) and ones using network analysis to study how a society operates (social network analysis in its most specific sense). For both of these, I’m aware of some early medieval studies and others that are potentially applicable to early medieval style-data. I’ll cover intellectual networks in this post (including a discussion of a recent IHR seminar) and then move onto social history uses of network analysis in the next post.

Intellectual networks/spread of ideas: example projects

1) Ego-networks
There are several forms that network analysis of intellectual networks can take. One obvious one is as a more quantitative version of what’s been done for many years (if not centuries): the study of “ego-networks”, the intellectual contacts that a particular individual has.

This is the basis for the study by Isabelle Rosé of Odo of Cluny (Rosé, Isabelle. “Reconstitution, représentation graphique et analyse des réseaux de pouvoir au haut Moyen Âge: Approche des pratiques sociales de l’aristocratie à partir de l’exemple d’Odon de Cluny († 942)”, Redes. Revista hispana para el análisis de redes sociales 21, no. 1 (2011)

Rosé’s study isn’t strictly of just an ego-network, since she also tries to analyse the connections that Odo’s contacts had with each other in which Odo wasn’t involved, but the centre is clearly Odo. Rosé uses a mix of different sources (narrative and charters) to construct snapshots of Odo’s connections over time: she ends up with a PowerPoint slideshow showing the network for every year (available from here). She wanted to include a spatial dimension to the networks (showing where connections were formed), but couldn’t find a way of doing that.

Rosé’s account includes some useful detail about her methodology. The data she collected in Excel consisted of 2 people’s names, a type of connection and a direction for it, a source and start dates and end dates for the connection. She also codes individual nodes based on the person’s social function (monk, layman, king etc) and the aristocratic group they belong to (Bosonids etc); this is reflected in their colour and shape on her network diagrams.

There are a lot of questions raised immediately about how such decisions are made (period of time allocated to a particular connection, how she decides on who counts as on one of the groups); all the kind of nitty-gritty that has to be sorted out for any particular project.

What does Rosé’s use of network analysis allow that a conventional analysis of how Odo’s social networks helped him couldn’t do? One is that the data collection method encourages a systematic searching for all connections that an unstructured reading of the sources might miss. Secondly, the visualization of networks (especially as they change over time) gives an easy way of spotting patterns, allowing periodization of Odo’s career, for example. Thirdly, it’s possible to compare different sorts of tie, e.g. she shows that the kinship networks (whether actual or the fictive kinship of godparenthood) consists of a number of unconnected segments. But when you include ties of kinship and ties of fidelity, you do get a single network. Finally, Rosé uses a few formal network metrics to rank people by their centrality to the network (their importance to it) and their role as cut-points (people whose removal from the network would mean that there were disconnected segments of it).

Apart from this restricted use of metrics, Rosé is mostly doing visualization and I suspect that many of her conclusions are confirmations of things that a conventional analysis of Odo’s social network without such complex data collection would have come up with anyhow: who Odo’s key connections were, the importance of the fact that right from the start Odo had connections to the Robertines and also the Guilhemides. But one of her most interesting comments was that analysis showed a move away from kings as central to social networks, which she connected to a move to “feudalism”. If we could find comparable data sets (and there are obvious problems in doing so), it’d be interesting to see whether kings outside France become non-central to reforming abbots in the same way.

2) Scale-free networks
There are a couple of articles I want to highlight which talk about scale-free medieval networks and which I want to discuss more for some of the difficulties they raise than the answers they’re coming up with. One is work that hasn’t yet been published, but has been publicised: analysis of the spread of heresy by Andrew Roach of Glasgow and Paul Ormerod. The other is Sindbæk, S.M. 2007. ‘The Small World of the Vikings. Networks in Early Medieval Communication and Exchange’, Norwegian Archaeological Review 40, 59-74, online.

But first, a very rough explanation of scale-free networks, which means introducing one or two basic mathematical/statistical ideas. The first is the degree of a node, the number of connections it has. The second is the distribution of these degrees, i.e. what percentage of nodes have 1 degree, 2 degrees, etc. Scale-free networks are ones where the degree distribution follows a power law: roughly speaking, you have a few very well-connected nodes and then a long tail of a lot of poorly-connected nodes.

The crunch here is “roughly-speaking”: there are all kinds of issues about whether any particular example really does represent the power law distributions that supposedly lie behind it. It’s a reminder that if we as historians we do start doing more of this kind of work, we’re probably going to need some good mathematicians/statisticians behind us pointing out possible issues.

Without seeing the data, it’s impossible to tell whether Roach and Ormerod are accurate about medieval heresy spreading through such types of networks. But Søren Sindbæk’s paper on Viking trade suggests that the interest here isn’t strictly whether we’re talking about scale-free distributions or not. It’s a more general question about how the very localized societies within which the vast majority of medieval people lived could nevertheless allow the relatively rapid long-range spread of everything from unusual theological ideas to silver dirhams.

Søren’s main point is that there are two possible ways that such small-world networks can evolve: either you can have a few random links between two otherwise largely separate networks (weak-ties model) or you can have a few very well-connected nodes amid the otherwise very localised societies (“scale-free”). Which of these two ideal type of networks you have affects considerably the robustness of the network: i.e. if you have one or two crucial hubs that get destroyed by attackers, the whole network falls apart, but random attacks aren’t likely to have much effect, while the weak-ties model is more vulnerable to a random attack (if a random link that ties two networks together happens to get severed). Søren tries to see which type of network best fits two very limited sets of data (one based on the Vita Anskari) and one on archaeological data. The answer, not surprisingly, is “scale-free” networks.

I say the answer isn’t surprising because the medieval world is full of hierarchies of people and places, and some of the defining characteristics of those at the top of such hierarchies are that they move around more or they have connections to a lot more places. I found Søren’s paper mainly revealing in giving a feel of the numerical bounds for where simple visualization is a useful tool: a plot of 116 edges (see Fig 3) is already getting complex to visualise; one with 491 edges (see fig 4) almost impossible to take in by eye.

As for Roach and Ormerod, the fact that heresy was mainly spread through a small number of widespread travellers isn’t exactly news. We’ll have to wait and see whether they can provide something that gives a new dimension of analysis.

3) Six degrees of not-Alcuin
Finally for this post, I want to discuss an IHR seminar I heard back in May: Clare Woods from Duke University talking about “Ninth century networks: books, gifts, scholarly exchange”. Clare’s coming to intellectual history from a slightly different angle from Isabelle Rosé: she has been editing a collection of sermons by Hrabanus Maurus for Archbishop Haistulf of Mainz, and thinking about how to represent the relationship between manuscript witnesses visually (rather than just rely on verbal descriptions or stemma diagrams.

The point here is that manuscript stemma can be thought of as directional networks between manuscripts, whose place of production can be located (more or less accurately). (There are also projects endeavouring to generate manuscript stemma automatically, but I’m not discussing those at the moment). Clare is also using data from book dedications, known manuscript movements, and the evidence of medieval library catalogues.

Also in contrast to Rosé, Clare was interested in the possibility of getting beyond the spider’s web idea of intellectual history. i.e. that Hrabanus (or Odo) sits at the centre and everyone else revolves around him. This is a particular issue for Carolingian intellectual history because of Alcuin. We have by far more letters of Alcuin preserved than of any other Carolingian author (Hincmar probably comes second, but his letters still haven’t been edited properly), so if you use Rosé’s techniques you’re liable to end up overrating Alcuin’s significance vastly.

Clare’s main focus was on simple tools for visualizing this information, ideally in both its spatial and temporal dimensions. As I said above, Rosé was using Excel, Powerpoint and NetDrawand was finding problems in showing locations. Clare was using Google Maps for the spatial element, but thought she’d need Javascript (which she doesn’t know) to show changes over time. I have seen projects which use GoogleMaps and a timeline, such as the MGH Constitutiones timemap (click on Karte to follow how Charles IV, the fourteenth century Holy Roman Emperor moved around his kingdom). I don’t know how that is made to work.

I’d be interested to know from more informed readers of the blog if there are such tools available that non-experts can use to produce geo-coded networks of this kind. Gephi seems to be popular free software for network analysis, and I’ve seen a reference to a plug-in for this which allows entering geo-coded data. The Guardian datablog recommends Google Fusion Tables.

But whatever software you have, there are the normal issues of data quality. There’s a particular problem with data coming from a very long timescale: in questions David Ganz wondered whether the evidence was getting contaminated by C12 copies (I wasn’t quite sure whether that’s just because there are so many manuscripts of all sorts from later). How do we know whether manuscript movements do reflect actual intellectual contacts, rather than just random accidents of them getting moved/displaced etc? Clare also discussed the problems of how you mapped a manuscript which came from “northern Italy”. Her response was to choose an arbitrary point in the region and use that – at the level of approximation and small number of data points she’s using, it’s not a major distortion.

The data sets for early medieval texts are always going to be tiny: having more than 100 manuscripts of one text from the whole of the Middle Ages is exceptional. (The largest transmission I know of is for Alcuin’s De virtutibus et vitiis of which we have around 140 copies). But Clare’s project does potentially offer the possibility of combining her data with other geo-referenced social networks to get an alternative and wider picture of intellectual connections in the Carolingian world. Combining data-sets is likely to lead to even more quality issues, but it does offer the possibility of building up new concepts of the Carolingian world module by module.

Trifle layers, puzzle boxes, and charter statistics

I’m around six months behind in blogging IHR seminars, and Jon Jarrett has already provided not only the text of his paper from June on “Managing Power in the Post-Carolingian Era: Rulers and Ruled in Frontier Catalonia”, but also pictures of the event. So instead, I want to use his paper and another much more recent one I heard at the IHR on Spanish charters to act as a springboard for thinking about how we might use charters to compare societies.

The second paper was Graham Barrett on “The Literate Mentality and the Textual Society in Early Medieval Spain”, and for me some of the most interesting parts of his talk were the statistical evidence. He was working from a corpus of around 4000 charters of 711-1031 from the Asturias-Leon and Navarra in northern Spain. And one of the key points he was making was that while the charter numbers went up from 850, there wasn’t an increase in the average number of royal charters per year, but there was one in ecclesiastical charters and the number of lay charters increased more or less steadily. In other words, this is a society where top-down notions of increasing literacy don’t work particularly well – the charter habit isn’t simply percolating down as a side-effect of governmental bureaucracy.

Similarly, Graham had statistics about scribes, showing how over the period there were an increasing number of scribes who were writing more charters, rather than most scribes only writing one or two charters, e.g. that we’ve got something that looks like the tentative start of royal and aristocratic chanceries. And he also thought it was possible to see different categories of scribes, in terms of who they wrote for: royal scribes, episcopal scribes, monastic scribes, aristocratic scribes and village scribes.

The point of both these two lots of statistics is that in theory they’re region-independent. You could take statistics from a completely different area of Spain (or Germany or France or England) and compare them and see if the same patterns are visible. So it might be possible to see whether patterns of top-down literacy do seem more plausible elsewhere, or whether the “professionalisation” of scribes varies in time across different areas. You can start to do comparative history with charters in a way that you can’t easily with just anecdotal or case study evidence.

Well, that’s the charter statistics, but where do the trifles and the puzzle boxes come in? These are two metaphors that have been used for looking at the structure of medieval societies. The first is from Susan Reynolds, Fiefs and Vassals (OUP, 1994), p. 40:

the layers of [medieval] society were more like those of a trifle than a cake: its layers were blurred, and the sherry of accepted values soaked through. Taking the whole of society…one has to see it as a very rich and deep trifle with a lot of layers

The other is from Jon’s talk at the IHR, where he described power in Catalonia as akin to a puzzlebox, in which only some of the holes lead to the ground. In some areas counts are visible directly interacting with the lower levels of society, in others they have to go through intermediaries. Looking at when/where that happens is one of the key issues in ideas about the tenth/eleventh century feudal mutation and the “privatization of power”. But the other way round – when/where do local networks start to connect into wider ones, it’s probably one of the main factors in the rise of the Carolingian empire. That’s Matthew Innes’ idea anyhow – that what the Carolingians succeed in doing is getting local societies connecting into court networks, without necessarily changing the families who are actually running these local areas.

So what would be very useful is if we can somehow start coming up with metrics or criteria for how important people that, again, we can use for cross-regional comparisons. The problem is, a lot of titles are very regionally specific, such as the Visigothic saio or the Breton machtiern. And while there are other criteria we can use, a lot of them aren’t really helpful in practice with the evidence we have. For example, Chris Wickham wants to call people peasants only when they’re personally doing some agricultural work (Framing the Early Middle Ages p 386), which is next to impossible to prove either way in the majority of cases. In contrast, Chris’ ideas about the scale of a person’s control over land do sound like one of the most promising ways to start to distinguish some of the layers of the trifle.

Such a statistical approach isn’t the only way we can approach charters; people have got a lot of interesting stuff out of considering individual charters or small clusters, but it might be worth going back now to some of the pioneering statistical studies such as the work by David Herlihy and Barbara Rosenwein and seeing what else we can do now with vastly more computer power and web 2.0 technologies.

A partial ninth century crisis 1: economies and polities

A few weeks ago I went to a conference organised by the McDonald Institute for Archaeological Research in Cambridge. This was the second in a series of four linked conferences on the theme of crisis, which look at fifth, ninth and fourteenth century Europe and finally at the concept of ‘crisis’ itself. The title of this one was ‘Crisis, what crisis? The long ninth century’.

When I say I went to the conference, I actually mean I went to half of it, because I was fitting it in round childcare. (This is the typical world of Magistra et Mater: a morning spent hearing about the archaeological evidence for Scandinavian expansion, an afternoon discussing My Little Ponies). So my report will be distinctly patchy, but I hope still of interest to those who couldn’t get there. The conference included both those working on material culture and those primarily working with texts. Although most of the papers included at least some of both kinds of evidence, the ways in which they thought about crisis tended to be rather different, so this post will be mostly about the archaeological papers with a second one on more textual evidence.

We started with an introduction by James Barrett on Vikings and collapse. He summarised the continuing debate about the Vikings: ‘minimalist’ views that saw them as having a relatively small impact and being a normal part of the ninth century world, as opposed to a more ‘traditional’ view that saw them as having a large and disruptive effect. Some of this, of course, as he pointed out, depends on where you’re looking at: studies of Viking ancestry in the Wirral have found a lot more evidence for it than for Ireland for example. He also cited Robert Dentan [Recent studies in violence: What’s in and what’s out. Reviews in Anthropology 37 (2008): 41-67] pointing out that scholars are only studying representations of violence and that the actual experience of it is horrific. So even if Viking violence isn’t as widespread or as distinctive as been previously thought, that was no comfort to its actual victims. (I’ll talk more about such issues of perception in the next post).

Barrett then went on talk about theoretical models of collapse, and considered how you might create typologies of this, along with the linked concepts of conquest and colonisation. He defined ‘collapse’ as ‘a qualitative shift between hegemonic, hierarchical and heterarchical power’, whether voluntary or involuntary. He also pointed out how politically charged such concepts were in the modern world, e.g. suggesting that environmental factors might have played a factor in the collapse of particular societies. Similarly, discussions about early medieval societies tend to connect too closely to the modern states located in the same regions: there is a shadow haunting Viking studies of racism and genocide.
What interested me most in his talk is about how the term ‘crisis’ to him, could be almost automatically converted into discussions of ‘collapse’. An archaeologist can look at collapse, probably more effectively than a historian can. Crisis, with its emotional, mental element, is trickier to see in material remains. So what can archaeology tell us about the ninth century?

I heard a couple of papers on economic aspects of the ninth century, both arguing that it was a time of expansion rather than crisis. First of all we had Richard Hodges on ‘Charlemagne minus Mohammed’. I’ve heard Richard Hodges before and found him difficult to follow, and this paper was the same, so if I’m mis-explaining his views and anyone more knowledgeable wants to correct me, feel free to. His overall take on the early Middle Ages is that there’s an agrarian take-off in the post-Roman world, starting in NW Europe and then only later getting to southern Europe. (I think he may have got this from bits of Chris Wickham’s research that I haven’t read yet). He then combines this with Michael McCormick’s ideas about continuing Mediterranean trade and Venice as the linch-pin between Birka and the Carolingian courts.

Getting onto the archaeological evidence, and how sites are now being redated, Hodges sees the North Sea emporia as largely declining pre-Viking – even the type B emporia are already in decline by the mid eighth century. But there are also other places appearing, it’s not simply about collapse. Ribe ends around 850, but Kaupang is taking off just then. (It was later mentioned by another speaker that dendrochronology at Hedeby shows a lot of new building work there at the end of the ninth century).

Hodges then moved onto Mediterranean evidence, which is now his main area of research. Italian cities in the seventh and early eighth centuries look largely abandoned. On the other hand, an emporium has now been found at Comacchio at the mouth of the Po, started around 675 and continuing until the late ninth century (it was possibly destroyed in 881) and with a sequence like the North Sea emporia. It seems to have been linked to monasteries in the Po valley, and there’s trade of good quality soapstone visible. All this suggests some kind of Adriatic trade system, and although Venice is small at the start of the ninth century, there’s a major church building programme in the ninth century, implying increased wealth.

There’s also evidence of a ‘rural renaissance’ in the Italian countryside after the collapse of the sixth and seventh centuries. Hodges mentioned the reoccupation of the littoral, places such as Cugnano in western Tuscany, where there seems to be rapid regrowth. He then went on to talk about the monastery of St Vincenzo al Volturno, which he’s excavated extensively. In the eighth century it’s a small monastery, then c792-808 it’s suddenly massively enlarged, with a palace and workshops and a big church. In the 830s-840s both the church and the workshops again gets enlarged and reworked, then the site is static for around 30-40 years and gets sacked in 881. Hodges paired this data with information on land donations to show a move from consumption to minor production. In the late eighth century the monastery is dependent on 1 big donor (the Beneventan royal family), then from around 800 starts having a large number of small donations (with a hiatus in the 820s and 830s). Hodges was suggesting that part of the reaching out to new donors was producing counter-gifts for them (hence some of the needs for workshops). In 881 the monastery was sacked by a Saracen emir. The emir seems to have been in cahoots with Bishop Athenasias of Naples – judging by a (much-later) chronicle, the sack was very carefully targeted to drive out the monks, while the servants changed sides. Athenasias subsequently got control of the monastery. In the questions afterwards, Hodges was suggesting parallels with San Vincenzo to other ‘monastic cities’ such as Fulda (which haven’t had their rural hinterland excavated). What we didn’t get this time was Hodges ideas’ about the direct responsibility of the Carolingians for all this – in fact, despite the title, I don’t think Charlemagne got mentioned at all.

Finally, he talked a bit about his excavations at Butrint, in Albania at the Straits of Corfu. It had evaporated as a town by the early C7, but then got redeveloped. 2 towers which have been found and which were sacked around 800 (the time Birka was taking off) had a lot of cullet (scrap glass) plus a few South Italian pots, suggesting it was being used as a storehouse. A new centre was built in a different location in Butrint in the ninth century and texts suggest an archon was based there.
Overall, Hodges was arguing for two phases of trade. At the start of the ninth century there’s trade of prestige goods – including Chinese jade found at San Vincenzo. By the end of the ninth there’s been a shift away from this small-scale presige trading to larger scale trade and the beginnings of real sustainability. This was also reflected in more stratified buildings in C9 AS England, the multiplication of Frankish silos (for grain storage) and the development of fortified small manors in Italy. Hodges saw this large-scale economy developing from the 840s onwards and powered by the Vikings and Arabs. In a slightly bizarre analogy, he saw these as the hedge fund managers of the early Middle Ages, demonized, but essential for paying the taxes keeping us going. (Surely it wasn’t the Vikings paying the taxes?)

The second paper on economic themes was by Søren Sindbæk on ‘Routes for crisis? Early medieval networks and the ninth-century ‘re-linking’’. He was arguing that a supposed economic crisis in C9 NW Europe didn’t actually happen. The crisis has supposedly been marked by a ‘silver famine’, the demise of emporia and Viking raids, all of which are linked together. Klavs Randsborg argued (“Les activites internationales des vikings: raids ou commerce?” Annales Economies Societes Civilisations 5, Septembre-Octobre 1981. 862ff) that a decline in the amount of silver in Scandinavia in the late C8 led to the Viking raids on England and Francia.

Sindbæk was arguing that there wasn’t actually a silver famine (although some of the evidence he was using, such as the size of hoards, didn’t convince the numismatists in the audience). Some emporia declined, but there were also towns expanding – the Danelaw centres took off in the 870s, the Quentovic mint continued, Dorestadt was replaced by Tiel and Hedeby, Dublin was founded, etc. There was no general crisis, but instead changes to communications networks, based mainly on navigation becoming routine. The Viking trade network which emerged in the mid ninth-century has been underrated, mainly because it didn’t involve ceramics (the Frankish fineware pottery trade actually declined), but instead such materials as ivory, metalwork and soapstone vessels. At the end of the C9 we have the first evidence for specialist cargo ships, which helped contribute to dramatically improved economic integration.

As this paper showed, one of the big problems in discussing whether there’s an economic crisis is distinguishing between a zero-sum game, in which the existing wealth just gets redistributed around Europe and the Middle East, and actual economic growth. In contrast, discussions of C9 political developments normally implicitly work on the basis that it was a good time for Vikings and a bad time for everyone else. A couple of papers about two different polities, however, started complicating this picture. Firstly, we had Jesse Byock on ‘Vikings and Iceland in the Ninth Century: Crisis, what Crisis?’ He is currently working on the Mosfell Archaeological Project which is doing an interdisciplinary study of a corner of SW Iceland, partly because it’s one of these unusual areas where you have literary texts which actually have a lot of specific landscape data.

We didn’t actually get much on the project, however, more general stuff about Iceland, which as he describes it ends up sounding like an early medieval time capsule, where a ninth century social order goes into an uninhabited place and then largely has continuity – no invasions, no Black Death etc. Iceland essentially has a European Iron Age economy of mixed farming and fishing, with the population mostly free farmers and small scale chieftains. One of the most interesting points Byock made is that at the time of the settlement there was a Scandinavian ‘social crisis’, with the growth of elites and states at the expense of farmers and old-style small-scale chieftains. Iceland looks like an offshoot from this, as a place where the losers during state-formation could end up. As a result you get a peculiar combination of a Scandinavian tradition of statehood, but also a ‘headless’ society, because of the class values of the settlers who don’t want a hierarchy of command. Byock suggested that such a polity could be called a ‘Free State’ more accurately than a ‘Commonwealth’, with some aspects of an embryonic state, but also the ‘evolutionary mechanism’ going into reverse, shedding the aristocratic strata.

All this makes Iceland seem like the ideal type of Chris Wickham’s golden age of the peasantry, but there’s a twist. Byock argued that while Scandinavia conformed to the model of Ester Boserup in which population increases led to technological development, Iceland looks very Malthusian. After the initial thrill (which he compared to the Oklahoma Land Rush) the settlers realised that Iceland had almost nothing anyone else wanted. As a result, material wealth was very limited: a longhouse site which reveals 30 buttons is a sign of unusual wealth. And Iceland was extremely prone to natural crises. The single most revealing graph was of Iceland’s population in the eighteenth century. It finished with around the same population as before – periods of growth were interrupted by several collapses, from disease, famine and the effects of volcanic eruptions. If Richard Hodges had given us Vikings as hedge fund managers, I couldn’t help thinking of the Icelandic banking crisis as another example of a failed attempt to prosper in a deeply hostile environment.

We then had a paper by Stephen Driscoll on ‘The archaeology of the Scottish Political Landscape: Viking Age Transformations’, which was talking about rewriting early Scottish archaeology in the light of how Pictish history has been rewritten by Alex Woolf and Dauvit Broun. In the traditional view the Gaels of Dal Riata under Kenneth MacAlpin take over or conquer the Picts in 843 and create a new Picto-Scottish realm, while the Britons of Strathclyde are nearly destroyed by the Vikings in 870, and the kingdom never really recovers – it’s only a sub-kingdom afterwards.

The new view is that the Pictish kingdom continues after Kenneth, but that it was relocated. The original kings of the Picts had been in Fortriu (which Alex Woolf argues is in the far north). This fits with the fact that there’s an awful lot of archaeological evidence there, including the important monastery of Portmahomack and the fort of Burghead. The Fortriu dynasty subjected Dal Rieta between 789-839, but then got destroyed by the Vikings. However the centre of Pictish power then moved south to Forteviot and continued until around 900.

Meanwhile, after the Viking siege of Dumbarton in 870, a new royal centre developed at Govan. There was Norse influence but this was via Gall-Gaidhel (Gaelic-speaking Norse) [They, of course, get everywhere eventually]. The Kingdom of Strathclyde seems to end up being bigger and more expansive than before. Driscoll then went on to discuss briefly the archaeology of a number of places linked with ninth century kings: Forteviot, Scone, Govan. What we didn’t get (perhaps through a lack of time) was any explanation of why the Picts abandoned both their language and their sculpture around 900 (the ninth century apparently wasn’t long in Scotland). That suggests more of a general crisis than earlier on, but it may be the kind of question that archaeology isn’t well-placed to argue. I probably need to settle down and read Alex Woolf for more details. One more thing onto the reading list…

I was initially thinking that the Scottish evidence might fit into a ‘survival of the luckiest’ narrative of the political effect of the Vikings. I think Gareth Williams was arguing this concerning AS England, in a paper I didn’t get to hear. The Vikings, as an outside force, disrupted existing political equilibriums by knocking out some competing kingdoms, allowing those that survived to expand. But in fact, neither the Pictish kingdom nor Strathclyde got finished off by the Vikings. The Vikings did create crises in Scotland: relocations of political centres are fairly major events, but the long-term results weren’t straightforward. Back to the drawing-board with the models.

IMC 4: my partial conversion to social physics

I’m just back from a week in Orkney, where the Middle Ages seems like a recent blip in a 5000 year history, so my next account of the International Medieval Congress in Leeds may be particularly disconnected. But I wanted to report (as requested) on the single most thought-provoking session I went to at Leeds: the round table on complexity science and the humanities.

It wasn’t strictly a round table, but instead a couple of presentations. The first was by Serge Galam who calls himself the first ‘social physicist’, but who was doing what I’d call mathematical modelling of opinion dynamics. The examples he was using were from modern elections (and he’s apparently been quite successful in predicting possible outcomes), but he was arguing that such models could also be used for the spread of religious belief.

I’ve always been suspicious of attempts to model human behaviour in this way, because they seem too simplistic, but what dawned on me in this talk was that even with a very basic model, you start getting non-intuitive results. Serge started with a simple yes-no or two party decision, and a framework of two separate mechanisms for opinion forming. One was external, acting directly on an individual (like marketing in elections), the other was internal, arising from the dynamics of interactions between people (referred to as agents here). He was just interested in the internal influences and used external factors to provide an initial parameter: the influence of the advertising produced initial conditions of say 24% of agents for the motion and 76% against. Serge then worked with a model in which there were three kinds of agents: inflexible (who never shift their opinion), floater (who has an opinion but is ready to shift if given more arguments by the other side) and contrarian (who wants to be different to the local or global consensus, regardless of what this is). He used a simplified model of opinion forming in which groups of these agents met at random and used a local majority rule – those agents whose views could change were changed based on the majority within the group. (This may actually be closer to election psychology than more high-minded views that people are independently convinced by the quality of the arguments). The groups were then reshuffled at random and the process repeated until a stable outcome was achieved.

If you had only floating agents, the outcome was fairly predictable: the initial majority always win over everyone. But the moment you added either contrarians or the inflexible, you got more interesting patterns. With a few contrarians (up to about 10%) you got a stable situation with a majority and a minority view. If you have more contrarians (more than about 17%), you end up with views splitting 50-50, even if one side started with a strong majority. Serge was arguing that contrarians were more common in the modern world (which seems intuitively plausible, though very hard to demonstrate), and that this posed a real problem for democracies, where you’ll increasingly get very close elections.

If instead of contrarians, you have inflexible agents, the dynamics are even more alarming, in some ways. If you only have inflexible people on one side, if there are more than 17% of them, their side will always win, whatever the initial conditions. (I thought of the 27% thinking George W Bush was doing a good job as president and winced). Of course, in practice there are inflexible people on both sides of most arguments, but the side with more inflexible people is definitely at an advantage, and can gain a large majority from a relatively unfavourable position.

A lot of the questions about Serge’s paper afterwards were pointing out the simplifications made in the model and asking about possible effects: if you don’t have random networks, if you have degrees of conviction, if you have opinion formers who have more influence on groups than others? It sounds like all these kind of details could be added onto the model (at the price of greater complexity of equations). The interesting question (which presumably only experiment would discover) is whether such changes actually affect the dynamics and change the final outcomes.

The bigger question for medievalists is whether such models are relevant at all. One objection was that Serge’s suggested application (of religious conversion) was irrelevant, because conversion in the period wasn’t a matter of free will, but coerced/forced. It seemed to me, however, that you could potentially still use this model for resistance to conversion. In most medieval conversion situations, only one side has coercive power: the Jews, the pagans, the heretics don’t normally have it. If you take religious coercion as an external factor, you can start thinking about how people decide whether or not to resist, how many religious zealots you need to maintain a faith, short of extermination. (I’d take the contrarians here to be sceptics, suspicious of whatever orthodoxy tells them).

For the early Middle Ages, of course, you still wouldn’t have the parameters you need for the model (though by the time you get to the Reformation, you might be able to get some meaningful figures). But even if there’s no direct application, the outcomes of these simplified models can possibly provide useful rules of thumb in showing how movements gain or lose support and that the dynamics aren’t entirely straightforward.

In the second paper, we got onto games: more specifically Stefan Thurner was talking about Pardus, the largest online game in Europe. This is a role-playing game in space, which cunningly doubles as a self-funding social science laboratory, by recording every click made. (Apparently, the student who originally designed it doesn’t need research funding, because he earns substantially more than a research stipend from selling premium accounts).

Stefan saw such a game as allowing social science to become an experimental science. The game allows economic, social, scientific and military activities, collaboration etc: it has no rules and no aims, allowing whatever people want to do within it (apparently banks, political parties and clubs have all spontaneously developed). The main interest of the researchers have been in how social networks have developed over time, and looking at whether social science theories of networks actually hold up.

What makes it even more interesting is that they’re not looking just at networks of friends or messaging networks (though both are included in the game and are being studied). It is also possible in the game to mark someone as your enemy. Enemy networks can thus be analysed, which prove to be intriguingly different to friendship networks (and which sound potentially very useful for anyone studying feuds) . For example, enemy networks seem to be formed by preferential attachment, whereas friendship networks aren’t.

There are also intriguing gender differences here. Players are self-identified by gender in the game. Friendship networks for those identified as women are more reciprocal than for men: if a ‘woman’ marks another ‘woman’ as a friend, the second is more likely to respond by marking the first as her friend, than in the same interaction between two ‘men’. On the other hand, if one ‘man’ marks another ‘man’ as his enemy, the second is more likely to respond by marking the first as his enemy than is the case between two ‘women’. (What this says about the characteristics of ‘men’ and ‘women’ is left to the reader…)

This isn’t the only attempt to use MMORPGs (Massively multiplayer online role-playing games) to analyse social behaviour: I recently saw a mention of a project using World of Warcraft to study gang dynamics. The latest plan of the Pardus researchers is to take their experiment one stage further and have a version of a similar game set in a historical world and with banks run by central bankers, to see what the effects of different central bank policies might be on economic behaviour.

The bigger question about Pardus, of course, is how generalisible the results are, given that the demographics are untypical. Maybe all it tells you is how a particular group of obsessives behave. The evidence so far, however, is encouraging: for example, messaging networks in Pardus look mathematically very like those in the real world (such as phone networks) even though they’re not from a representative social sample. If we can find other networks that are similar (and the possibility exists of finding these even for the early Middle Ages, via charter witness lists, for example), it seems reasonable to start applying some of the other Pardus results, or at least using them as working hypotheses.

I didn’t get to hear the questions put to Stefan (since I had to go and develop some real-life networks at the bloggers meet-up), but the possibilities offered by both researchers did seem intriguing to me. Not something I have the time to explore at the moment, but definitely worth checking back on in a few years time.