Historical networks session at Sunbelt

November 23, 2016

Sunbelt is the anual social network analysis conference, and for a few years now it’s been host to history and archaeology sessions. Do consider contributing to this year’s session, I was told by the organisers that archaeology talks are very welcome.

What? History session at Sunbelt

Where? Beijing

When? 30 May – 4 June 2017

Deadline 10 January

Session on “Historical Network Research” at Sunbelt 2017 in Beijing, 30 May – 4 June 2017

The XXXVII Sunbelt conference of the International Network for Social Network Analysis, held in Beijing from 30 May to 4 June 2017 (http://insna.org/sunbelt2017/), will host a panel dedicated to Historical Network Research. All scholars interested in presenting a paper or poster within this session are cordially invited to submit an abstract by 10 January 2017 8 p.m. EST = 11 January 2017 1 a.m. Greenwich Mean Time through the conference website. Guidelines for the abstract, travel & accommodation information, FAQ, and the submission form are available at http://insna.org/sunbelt2017/ and the abstract submission is now open. The conference does not require submitting the text of the paper at any stage, only the abstract is needed. The abstract should be 200-500 words long (the limit of the relevant field in the form is about 1,400 characters), and should not contain bibliographic references. When submitting your abstract, please select “Historical Network Research” as the session title in the relevant drop-down menu.


Historical Network Research: Session Abstract

The methods of Social Network Analysis (SNA) have recently started to find their place in the historians’ toolkit, thus giving birth to the burgeoning discipline of Historical Network Research (HNR). After a successful series of smaller workshops devoted to HNR, an international conference explicitly focused on HNR was held in Hamburg (2013), followed by conferences in Ghent (2014), Lisbon (2015), and Turku (upcoming 2017). In addition, sessions devoted to the application of SNA to historical research have been organized at Sunbelt since 2013, and at EUSN since 2014. In 2016, the institutionalisation of HNR was marked by the creation of a new academic journal, the Journal of Historical Network Research (http://historicalnetworkresearch.org/journal/), whose first issue will be published in the summer of 2017.

The aim of this session is to contribute to this emerging field by bringing together historians and other scholars applying SNA to their respective research areas, and by enhancing international and interdisciplinary exchange. We invite papers that explore the application of the formal methods of SNA to historical research and/or delve into the added value of this approach. Topics may include, but are not limited to, network analyses of historical data (from any period) on social, political, and religious groups, movements, cliques, and organizations; communication; economic and intellectual exchange; kinship; social and political upheavals, conflicts, wars, and peace-making; the diffusion of representations, practices, and artefacts through social networks; the reconstruction of past social networks through material culture; etc.


Session organizer:

David Zbíral, Masaryk University, david.zbiral@mail.muni.cz


Session chairs:

Delfi I. Nieto-Isabel, University of Barcelona, delfinieto@ub.edu

David Zbíral, Masaryk University, david.zbiral@mail.muni.cz

CFP: archaeology-history session at EU SNA conference in Paris.

January 27, 2016

eusnaIt’s with great pleasure that we can announce the first ever conference session which is organized by the Res-Hist, The Connected Past and the Historical Network Research group:

Historical and Archaeological Network Research

Submission deadline 16 February 2016.

Submissions via the conference website.

Network analysis, be it inspired by sociology or physics, is making its way in historical and archaeological research on all periods and topics. Over the last decades, a substantial number of studies has shown that both network theories and network methods derived from other disciplines can be fruitfully applied to selected bodies of historical and archaeological data and go beyond the metaphorical use of network-related metaphors. However, most of this work has paid little attention to the specific challenges skills of historical and archaeological research, e.g. concerns with sources, missing data, data standardization, as well as the situation of networks in time and space.

In recent years, a burgeoning community of historians and archaeologists have taken on these challenges and begun to adapt and develop formal network techniques to address the substantive questions and challenges key to their disciplines. This has been made possible thanks to collaboration and interaction with scholars from other disciplines.

The aim of this session is to further develop this community by promoting contacts between the various disciplines that aim at making sense of past phenomena through methods derived from network analysis; and between the various geographic and language-based communities in Europe.

We welcome papers on any period, geographical area, and substantive topic, using any network research method. The authors may by historians, archaeologists, as well as scholars from other disciplines. To be eligible, the proposals should:

  • Address and clearly formulate research questions concerning past phenomena.
  • Critically address issues related to the sources/materials/construction of data used.
  • Explain why it is substantively interesting to consider their topic in formal network terms (i.e. as ties between nodes), what the added value of such a view is, and what methodological choices it implies.

Paper which address questions related to time or space in networks are encouraged but not a requirement.

This call for papers is jointly issued by The Connected Past, Historical Network Research, and Res-Hist – but feel free to submit if you don’t know any of these groups! It will be an opportunity to meet them.

The working language for the conference will be English, but the organizers will be happy to help those who do not feel confident with their English during the discussions. Please note that the oral presentation will be short (ca. 15 minutes, as there will be at least 4 papers per 2-hour time slot, and we want to keep some time for discussion). The papers are not intended to be published together. Feel free to present either work in progress, so as to receive useful suggestions, or work that has already been published, but not in English or not widely circulated: the EUSN will allow a wider audience to discover your research.

The proposals will be selected by: Tom Brughmans (University of Konstanz); Marten Düring (CVCE, Luxembourg); Pierre Gervais (University Sorbonne Nouvelle Paris 3, Paris); Claire Lemercier (CNRS, Sciences Po, Paris).
Proposals can be submitted via the conference website.

CFP 10th Historical Network Research workshop

November 6, 2015

Via the Historical Network Research mailing list. The main language of the meeting is in German but English presentations are welcome.

Alpen-Adria-Universität Klagenfurt / Heinrich-Heine-Universität Düsseldorf, Institut für Geschichtswissenschaften, Lehrstuhl für Geschichte der Frühen Neuzeit:

Florian Kerschbaumer / Dr. Tobias Winnerling

28.04.2016-30.04.2016, Düsseldorf, Haus der Universität

Deadline: 25.11.2015

Call for Papers

Fakten verknüpfen, Erkenntnisse schaffen? Historische Netzwerkforschung in Wissens- und Wissenschaftsgeschichte

Wissenschaft lebt von der Vernetzung. Das Klischee des einsamen Denkers, der isoliert von der Umwelt in seiner Experimentierstube arbeitet, trifft in den seltensten Fällen zu. Wissenschaftliche Erkenntnis entstand in der Regel im Austausch zwischen Wissenschaftlern, im Dialog oder im Streit. Auch der Aspekt der Konkurrenz unter Wissenschaftlern um eine Erkenntnis spielt in diesem Kontext eine Rolle. Kurzum, Wissenschaftler arbeiten in Netzwerken.

Zur Analyse dieser Netzwerke liegt es nahe, sich auf die in den vergangenen Jahren zunehmend populär gewordene Methode der historischen Netzwerkforschung zu beziehen. Lässt sich das Phänomen der Wissenschaft netzwerkanalytisch fassen oder eingrenzen? Wie kann die Komplexität historischer Interaktionen und Akteure im wissenschaftlichen Feld angemessen einbezogen werden? Wie können Konzepte visualisiert und analysiert werden, die sich über die Ebene reiner Personenbeziehungen hinauswagen und als 2-mode, 3-mode … n-mode-Netzwerke angelegt sind? Gerade in der Wissenschaftsgeschichte genügen einfach Person-zu-Person-Netzwerke nicht; es müssen Fragen des Verhältnisses dynamischer (Personen, Institutionen) und statischer Entitäten (Orte, Objekte), individueller (Personen) und kollektiver Akteure (Institutionen, Verbände, Parteien, Gruppen), von Akteuren und Ereignissen (Kongresse, Feste, Begräbnisse), von Produzenten, Produkten und Produktionsstätten (etwa Autor – Verlag – Buch – Ort) und der Wechselwirkungen zwischen all diesen geklärt werden. All diese Möglichkeiten der Konstruktion sinnstiftender Zusammenhänge treffen in der Wissenschaftsgeschichte aufeinander – vielleicht noch mehr.

Daraus ergibt sich die Frage nach den Strukturen, Prozessen und Inhalten der Netzwerke und ihrem Wandel:

Strukturen: Gibt es spezifische Unterschiede zu anderen (nicht-wissenschaftlichen) Netzwerken? Wer waren die Träger der wissenschaftlichen Netzwerke? Welche Rolle spielten Einzelpersönlichkeiten, welche Rolle spielten Institutionen (Vereine, Universitäten, Wissenschaftsorganisationen)?

Prozesse: Wie entstehen wissenschaftliche Netzwerke, wie werden sie erhalten und warum verschwinden sie irgendwann?

Inhalte: Wie hängen wissenschaftliche Erkenntnis und Netzwerke zusammen? Gibt es Unterschiede zwischen den Disziplinen der Wissenschaft?

Der Workshop ist die 10. Veranstaltung der Reihe „Historische Netzwerkforschung“, die bereits seit 2009 ForscherInnen aus allen Bereichen eine Plattform zum Austausch über neue Projekte, Entwicklungen und Techniken im Kontext der Historischen Netzwerkforschung bietet.

Eingesandt werden können daher – ganz im Sinne der Tradition der Veranstaltungsreihe – Vorschläge für Vorträge, die sich in theoretischer und/oder praktischer Hinsicht mit den oben skizzierten Problemen befassen, aber auch zu Projekten der Historischen Netzwerkforschung, die über den hier genannten Themenschwerpunkt hinausgehen. Alle wissenschaftlichen Disziplinen und theoretischen Zugänge sind dabei gleichermaßen willkommen, kreative Herangehensweisen ausdrücklich erwünscht.

Vorschläge für mögliche Präsentationen bitten wir bis zum 25. November 2015 mittels Abstract (ca. 300 Wörter) an winnerling@phil.uni-duesseldorf.de zu senden. Wir bemühen uns um eine Finanzierung der Reise- und Übernachtungskosten, können dies jedoch zum jetzigen Zeitpunkt noch nicht garantieren.

Neben den Vorträgen wird es auch einen Einführungsworkshop in die Historische Netzwerkforschung sowie einen Workshop für Fortgeschrittene geben. Genauere Informationen hierzu werden noch zeitnah angekündigt. Für die Workshops freuen wir uns auf alle Interessierten und laden herzlich zur aktiven Teilnahme ein! Aus organisatorischen Gründen bitten wir auch hier um Voranmeldung unter  winnerling@phil.uni-duesseldorf.de.

Réseaux et Histoire: because it will do you good to network in Foreign

September 18, 2015

executive-511706_640It’s necessary to frequently remind ourselves that Academia does not just happen in English. It sounds like a silly thing to write, but having worked in the UK for a while I know it is rare to attend events that are not in English and it is common to ignore scientific communities and publications in other languages. This attitude is certainly encouraged by the Institute of Scientific Information (creators of our beloved Impact Factor) who rarely incorporate non-English language publications in their index. This is an assumption supported by some generalizing statistics: the majority of scientific publications are in English, the vast majority of citations are to publications written in English.

There is nothing wrong with one language emerging as the dominant one to facilitate academic communication. But this trend is inevitably accompanied by other language communities producing, debating, and evaluating work in English and their own language. This is necessary and facilitates non-English speakers to evaluate and contribute to international debates. Such communities enable those who are engaged in both international and national debates to cross-fertilize academic communities. Most importantly however, these will be the communities that take care of one of our most crucial duties as academics: to communicate our findings in a critical and understandable way to the general public, regardless of their language.

All of this is of course beside the point 🙂 I want to encourage everyone to attend the third French-speaking historical network science community conference. It’s a great and active community, with some genuinely nice and interesting people. This will not be a disappointment. I have engaged with this community before and came out with fresh ideas and approaches I could not have possibly gained within my English-speaking cocoon.

When? 29-31 October

Where? Paris

Information? Website

The third conference of the French-speaking group Res-Hist (réseaux et histoire – historical network analysis) will take place in Paris on the 29-31 October. The format mostly offers discussions of work in progress by historians, as well as presentations by specialists of other disciplines (geography, geomatics, sociology, law, anthropology,  computer science) who have dealt with social networks in time, or social networks reconstructed from written sources. All those among you who understand French are welcome! Extended abstracts are put online when we  receive them: feel free to comment on our website http://reshist.hypotheses.org, that also gives details on the conference program.

Book: support networks for persecuted Jews in WWII

July 22, 2015

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.

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

July 17, 2014

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



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

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

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


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

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

References mentioned:

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

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

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

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

Archaeological and historical network analysts unite!

July 10, 2014

315px-I_Need_You_on_the_Job_Every_Day_-_NARA_-_534704Network science is becoming more commonly applied in both archaeology and history. But this is not happening without difficulties. Pioneers in both disciplines are now trying to overcome the numerous challenges that still surround their use of network techniques: how to deal with fragmentary data, performing analyses over extremely long time spans, using material data in network science to understand past human behaviour, …. I believe archaeologists and historians should face these challenges together! Through collaboration we might come to a better understanding of the use of network science in our disciplines much faster. In a recently published article in Nouvelles de l’Archéologie, Anna Collar, Fiona Coward, Claire Lemercier and myself show how many of the challenges that archaeologists and historians have identified are actually not discipline-specific: we CAN collaborate to tackle them together. Since this article is in French I wanted to provide an English summary of our argumentation here (written with my co-authors). The full article can be downloaded on Academia or through my bibliography page.


One of the key aspects of historical sources, compared to archaeological sources, is that the former often allow for the identification of past individuals, by name, and by role. This richness of data at the individual level means that network analytical methods can be very powerful in the illumination of past social networks and the details of particular places and times – offering, where the data are good enough, a window onto past social lives and interactions, and allowing the synchronic analysis of social networks at a particular moment in time.

However, the issues most commonly mentioned by historical network analysts also concern problematic and incomplete data. These issues are undeniably more significant for archaeology and history than for contemporary social sciences such as sociology. But we should not overestimate their potential impact. Even sociological research in contemporary populations face similar issues where full data may not be available for a variety of reasons, and although the problems are clearly more fundamental in history and archaeology, this also means that researchers in both disciplines have long been accustomed to dealing with, and developing methods at least partially compensating for, partial and biased datasets. As a result, this may be one important area where archaeology and history can contribute its expertise to other disciplines working with imperfect network data.


In contrast to history, archaeology is much less frequently furnished with such focused evidence. In archaeology, individuals are typically identified indirectly through the material remains they leave behind, and even where they can be identified, they often remain without names or specified roles.  Not only is archaeological data typically not ‘individualized’, but it can also rarely be attributed an exact date. Most archaeological data typically has date ranges with differing probabilities attached to them, making the establishment of contemporaneity between entities/potential nodes in networks (e.g. individuals; events; settlements) highly problematic. Because of this, archaeologists have tended to focus on the synchronic study of human behavioural change over the long-term, rather than on the diachronic examination of behaviour and interaction. A further characteristic of archaeological data is that it is also likely to be more strongly geographically grounded. Indeed, the geographical location of archaeological data is often among the few pieces of information archaeologists possess. Finally, network analytical methods in archaeology tend to focus most closely on long-term changes in the everyday lives of past peoples.

Common challenges in archaeology and history

Alongside these differences, there are also a number of common challenges facing archaeology and history, as ultimately both disciplines aim to achieve similar goals relating to understanding past interactions and processes.

The most significant of these common challenges are the fragmentary datasets that often characterize both disciplines; we typically deal with bad samples drawn from populations of unknown size and/or with unknown boundaries, snapshots of the past that are heavily biased by differential preservation and/or observation effects. However we argue that this does not exclude the use network techniques in our disciplines, nor does it limit us to only those research contexts for which high quality datasets are available.

A second issue facing our disciplines is that many methodological and theoretical network approaches have been developed in other disciplines to address particular research themes. As a result, they therefore function according to certain rules and/or have certain specific data requirements that might prevent straightforward applications in our disciplines.

Furthermore,  using a network approach to study a past phenomenon necessarily requires a researcher to make a series of decisions about how the parameters of that phenomenon should be represented – for example, what entities to use as nodes and what forms of relationship to model as vertices. Archaeologists and historians familiar with the analytical and visualization techniques used by researchers studying modern phenomena may find many analytical approaches and visualization techniques that are not appropriate or achievable. The past phenomena we are interested in, the kinds of questions our data allows us to ask, and the often very specific parameters of human behaviour assumed by archaeologists and historians for investigating the past, are likely to mean we will ultimately need to develop purpose-made visualization and analysis techniques. At the least we will need to acquire a critical understanding of the various methods available if we are to represent archaeological and historical network  data in appropriate ways – and indeed, to ‘read’ such visualizations and analysis results correctly.

Finally, the poor chronological control characteristic to a certain extent of historical and to a much greater extent of archaeological datasets, limits our knowledge regarding the order in which nodes and links in networks became salient and also the degree of contemporaneity between nodes. This is likely to have significant ramifications for the ways in which archaeologists and historians visualize and analyse networks, driving a need to consider ‘fuzzy’ networks, margins of error and probabilistic models, as well as the consideration of complex processes of network change and evolution over time.

Unite! Meeting the challenges together

In the recent surge of network applications in archaeology and history, it would seem that the two disciplines have thus far focused their efforts on the more obvious potential applications which mirror those most common in other disciplines, such as the identification and interpretation of ‘small-world’ network structure or the choice of datasets that are readily envisaged as or translated into network data (e.g. road and river networks). Such analyses have demonstrated the potential of the methods for archaeological and historical datasets; however, we believe that potential applications go far beyond this, and that network approaches hold a wealth of untapped potential for the study of the past. To achieve this potential, we will need to become more critical and more creative in our applications, and explore not simply what network science can offer the study of the past, but also what our disciplines offer in terms of developing that science – firstly to tackle specifically archaeological and historical questions, but ultimately to broaden the scope of the science itself as methodologies specifically developed for use in archaeological and historical contexts are taken up for use in tackling similar questions in other disciplines.

TCP (2013_05_12 19_17_14 UTC)Initiatives like The Connected Past and Historical Network Research offer a platform that would allow for exactly this kind of interaction between network scientists and those applying network science to the study of the past. The challenges individual members were encountering in our own research across archaeology and history encouraged us to consider developing a mutually supportive space in which to share concerns and problems, and to discuss ideas and approaches for moving beyond these.

We suggest that simply bringing people together through conferences, workshops, conference sessions and more informal groupings is key to fostering the dialogue between the disciplines that is so important to move forward applications of network analysis to the study of the past. Talking to each other across traditional disciplinary boundaries is vital in the ongoing development of network perspectives on the past. However, as noted above, at the same time we also need to be more sensitive to the specific demands of our disciplinary goals and our datasets and develop new network methods that suit our disciplines better. The sociological roots of most social network analysis software packages means that these are often designed and engineered to address discipline-specific research concepts that may not be appropriate for archaeology and history. SNA software has generally been created to deal with interactions between people in a modern setting – where the individual answers to questions about interactions can be documented with a degree of accuracy. As such, this software and network methodologies in general will need to be applied with care and ideally even developed from scratch for use with networks comprised of nodes which are words, texts, places or artefacts, for the characteristically fragmentary and poorly chronologically controlled datasets of archaeology and history, and for research that aims to go beyond the structuring of individual networks of contemporary nodes to investigate questions of network evolution and change. While interdisciplinary dialogue is crucial, we will need to be sensitive to the discipline-specific idiosyncracies of our data and to critique rather than adopt wholesale practices used in other fields. In this way, rather than apologizing for the ‘deficiencies’ of our datasets in comparison with those characteristic of other disciplines, we will also be able to make novel contributions to the wider field based on the new questions and challenges the study of the past offers network science.