CFP social network analysis Middle Ages

This event will be of interest to readers of the blog.



International Medieval Congress,

University of Leeds,

4-7 July 2022

Social Network Analysis Researchers of the Middle Ages (SNARMA) is looking for proposals for a strand entitled ‘Network Analysis for Medieval Studies’ at the International Medieval Congress at Leeds in 2022. The precise number of sessions and themes of each session will be decided based on the submissions. We would like to encourage the submissions to be as interdisciplinary as possible: the strand is very much open to those working on networks in language, literature, archaeology, etc., as well as history. We would also like to encourage submissions spanning the whole breadth of the Middle Ages chronologically. Papers may be focussed on particular case studies or on methodological questions such as the challenges proposed by fragmentary sources. We hope to present sessions which showcase a variety of different historical source types, such as charters, letters, chronicles, literary sources, and so forth. Papers should engage with either mathematical social network analysis or the theory of social network analysis.

Please email with a title and abstract up to 250 words, as well as you name, position, affiliation, and contact details, by 1 Sept. 2021

Topics may include but are not confined to:

  • Using SNA to define borders within datasets
  • Temporal, dynamic, or stochastic networks
  • Geographical networks
  • Diffusion models of disease spread
  • Diffusion models of religious beliefs
  • Data modelling with historical sources
  • Opportunities and challenges of assigning motivations to historical actors using social network theory
  • Digital prosopography and SNA
  • Advantages and disadvantages of particular software packages
  • SNA as a visualization tool
  • SNA as an heuristic tool
  • ‘Learning curve’ issues in the Humanities
  • Networks of:
    • Objects or artefacts
    • Manuscripts or texts
    • Political elites
    • Kinship and marriage
    • Trade and commerce
    • Block modelling with medieval communities
    • Religious dissent or pilgrimage/ cults of saints
    • Literary worlds; eg. Norse sagas or French chansons de  geste

NetSci/Sunbelt deadline January 24th

Submit your abstract to our session on archaeological and historical network research at NetSci/Sunbelt 2021 🙂

Deadline January 24th

Submission link:

Via the HNR newsletter:

The session “Networks and the Study of the Human Past” is part of Networks 2021: a joint Sunbelt and NetSci Conference. The conference takes place in Washington D.C. on July 6-11, 2021. The organisers are planning a hybrid in-person and remote (online) conference.

You can find the session “Networks and the Study of the Human” under number 19 in the list of organized sessions for Networks 2021. Deadline for submissions is January 24, 2021.

Networks and the study of the human past 

A growing number of studies in history and archaeology have shown that network research can constructively enhance our understanding of the human past. Moreover, it is becoming clear that archaeological and historical data sources pose interesting challenges and opportunities to social network analysis and network science. How did human social networks change over huge timescales? How can old texts and material artefacts help in answering this question? The aim of this session is to present new findings and approaches within historical and archaeological network research, and promote contacts between the various disciplines that approach past phenomena using methods derived from network analysis and network science.

This session explores the challenges and potential posed by such network studies of past phenomena, including: network modelling of past phenomena; data collection from archival evidence; incomplete and missing data; computer-assisted network extraction from texts; big data analytics and semantic network analysis based on fragmented sources; material sources as proxy evidence for social phenomena; exploration of long-term changes in past systems vs. mid-term or short-term processes; etc.

The session invites contributions from various disciplines applying the methods of formal network analysis and network science to the study of the human past. We welcome submissions concerning any period, geographical area and topic, which might include but are not limited to: migration; interpersonal relations; economy; past revolutions; covert networks of the past; industrialization; transport systems; diffusion processes; kinship; conflict and conflict solving; religion and science.

Session organizers:

Julie M. Birkholz (Ghent University & Royal Library of Belgium), Tom Brughmans (Aarhus University), Marten Düring (University of Luxembourg), Ingeborg van Vugt (University of Utrecht), Martin Stark (ILS Dortmund), David Zbíral (Masaryk University)

Jobs: 6 postdocs Social Network Analysis

Readers of this blog might be interested in these jobs (Via Humanist).

Deadline for applications 19/02/2020.

We are currently recruiting 6 Post-doctoral Research Fellows with
expertise in social research methods to work within the Trento Center
for Social Research Methods.

Computational/digital sociology and social network analysis
Two post-doctoral research fellows for researchers with experience in
computational/digital sociology and social network analysis. This
includes, among others:
·       computational methods for “statistical learning”, using R or Python,
·       design and analysis of experiments, including field and online
experiments and use of digital devices (e.g. smartphones, wearables),
·       advanced social network analysis and recent developments in
ERGM, SAOM/SIENA, multilevel and multimodal networks, large-scale networks,
·       The quantitative analysis of texts through text mining and the
use of techniques such as LDA (Latent Dirichlet Allocation), CTM
(correlated topic model) and LSA (latent semantic analysis)
·       the simulation of social phenomena with agent-based modelling (ABM).

For more details, please

The application deadline is: 19/02/2020, 12:00 (noon), CET.

CfP:Networks and the study of the human past at the 2020 Sunbelt conference in Paris

The History and Archaeology sessions at the annual Sunbelt SNA conference are becoming a strong tradition. Submit your abstract now.

Via HNR mailing list:

CfP:Networks and the study of the human past at the 2020 Sunbelt conference in Paris

Dear All,

please consider submitting an abstract for the Paris Sunbelt 2020 session on Networks and the study of the human past.

Deadline: 31 January 2020

Organizers: Julie Birkholz (Ghent University, Belgium), Henning Hillmann (University of Mannheim, Germany), Martin Stark (ILS, Dortmund, Germany), Bernd Wurpts (University of Lucerne, Switzerland)

Session Description:

Most network research focuses on contemporary data and is presentist in orientation, overlooking the vast store of interesting data from the past. The aim of this interdisciplinary session is to further extend the community of scholars working with historical data by promoting contacts between the various disciplines that aim at making sense of past phenomena through methods and theories derived from network analysis and network science.

We are looking for papers exploring the challenges and potential posed by such network studies of past phenomena. Examples of such challenges and avenues include, but are not limited to: selective samples; missing data; big data and textual/semantic network analysis based on sources of the past.

The session invites contributions from researchers from various disciplines applying the methods of formal network analysis and network science on the human past. We welcome submissions concerning any period, geographical area or topic. The authors may be archaeologists, historians, social scientists or economists, as well as scholars from other disciplines working with historical or archaeological data. Thus, the content of the networks may include but is not limited to: past revolutions; migration; industrial revolution; diffusion processes; transitions from authoritarianism to democracy; international trade; kinship; war; religion and science.

For more information use the following link:


We hope to see you in Paris!


Bernd Wurpts, Ph.D.


Department of Sociology

University of Lucerne

EU SNA call for sessions and workshops

What? An awesome conference full of Europeans (others also welcome) and network addicts

Where? Paris

When? June 14-17 2016

Deadline call for sessions and workshops: January 11 2016

Call for Workshops and Organized Sessions for the second European Social Networks Conference, Paris, June 14-17, 2016 (

Dear all,

We now invite you to submit proposals for organized sessions and workshops for the second European Social Networks Conference, which will be held in Paris from June 14 to 17, 2016 (see This European conference has received a regional endorsement by the INSNA.

You can propose to organize:

* A session, a set of paper presentations centered around a specific theme, for which participants can submit abstracts early March. Organized sessions consist of at least one 2-hour time slot accommodating 4-6 paper presentations.

* A workshop. Workshops are sessions of half a day (3 hrs) or a full day (2 sessions of 3 hrs) focused on teaching attendees specific methods, software or theories. These workshops are not free and require additional payment, namely 37.5 euro for half-day workshops and 75 for full-day workshops (with discounts for students).

Please send your submissions for sessions and workshops NO LATER THAN THE 11TH OF JANUARY, 2016. A call for abstracts will go out a week later. Please do NOT send abstracts for paper presentations and posters before January 19, 2016.

To submit an organized session or workshop, go to:

and follow the instructions.

Decisions will be communicated to the corresponding organizer(s) before January 19.

The call for abstracts, paper presentations and posters will be announced on the SOCNET list in the last week of January. Please check the website for updates regarding the EUSN conference. Do not hesitate to contact us at the email address below for any questions about the submission procedure.

Looking forward to seeing you in Paris next June!

The Program Committee of the EUSN 2016,
Laurent Beauguitte, Emmanuel Lazega, Christophe Prieur, Paola Tubaro

CFP Sunbelt SNA session challenges in archaeological network science

sunbeltI have attended the Sunbelt Social Network Analysis conference only once, in Hamburg two years ago. But it was a brilliant experience and so different from archaeological conferences (and not just because of the traditional two evenings of unlimited open bar). The conference is attended by mainly sociologists and statisticians with a good proportion of mathematicians, computer scientists and physicists. In the last few years there have been annual historical and archaeological network science sessions. So the number of historians and archaeologists attending the event are increasing. I can definitely recommend attending Sunbelt, and of course you should present in our session 🙂

I would like to bring the session ‘Challenges in Archaeological Network Science’ to your attention. The session will be held at the Sunbelt Social Network Analysis conference in Brighton on 23-28 June 2015. We welcome all abstracts that address the challenges mentioned in the session abstract below.

The deadline for submissions is 31 March 2015. Please visit the Sunbelt website for more information and to submit an abstract:

Please ensure to select the session ‘Challenges in Archaeological Network Science’ during the submission process. Feel free to notify us if you decide to submit an abstract.

We look forward to meeting you in Brighton,

Termeh Shafie and Tom Brughmans


Challenges in Archaeological Network Science

The application of network analysis in archaeology has only become more common in the last decade, despite a number of pioneering studies in the 1960s and 70s. The use of different techniques for the analysis and visualisation of network data has already led to new insights into past human behaviour. However, this renewed interest in network science is also accompanied by an increasing awareness of a number of methodological challenges that archaeological network scientists are faced with. These include, but are not limited to the following:

– How to deal with spurious data?

Sampling strategies in archaeology are often dominated by the geopolitical and financial constraints of excavation campaigns. Moreover, differences in the preservation of different materials provide a very fragmented picture of past human behaviour. As a result, networks constructed from archaeological data can be very sparse with apparent uncertainties.

– How to introduce more complex assumptions concerning tie dependency in the reconstruction of archaeological networks?

Network modelling is based on hypotheses from archaeological theory which in turn is based on archaeological evidence. A major challenge is how to infer the structure of an archaeological network given a set of assumptions regulating the occurrence of ties.

– How to deal with the poor chronological control of archaeological data?

The contemporaneity of observations and the exact sequence of events are often uncertain. This is problematic for network science techniques that assume node contemporaneity or require knowledge of the order of events.

– How to consider complex socio-spatial phenomena?

Archaeologists commonly study the spatial distribution of their data and evaluate to what extent spatial constraints influenced human behaviour. A limited number of spatial network techniques are currently available and many of these are not or hardly applicable in archaeology (e.g. network analysis of road networks).

This session invites papers that address these or other methodological challenges that network scientists in archaeology are faced with.

This session is organized by and will be chaired by:

Termeh Shafie,, Department of Computer & Information Science, University of Konstanz.

Tom Brughmans,, Department of Computer & Information Science, University of Konstanz.

SNA summer school Trier

trierGerman speakers interested in learning more about social network analysis might be interested in the Trier SNA summer school. You can sign up until 31-07-2014. More info on the website and below.

8. Trierer Summer School
on Social Network Analysis


Die „Trierer Summer School on Social Network Analysis“ findet dieses Jahr vom 29. September bis 4. Oktober 2014 (Mo.-Sa.) an der Universität Trier statt. Die Veranstaltung bietet in einem einwöchigen Intensivkurs eine umfassende Einführung in die theoretischen Konzepte, Methoden und praktischen Anwendungen der Sozialen Netzwerkanalyse. Sie besteht aus zwei aufeinander aufbauenden Modulen sowie mehreren zusätzlichen Workshops zur qualitativen und quantitativen Netzwerkanalyse. Zudem bieten die Dozenten individuelle Forschungsberatungen an.

Die 8. Trierer Summer School ist als Einsteigerkurs konzipiert. Sie richtet sich vor allem an Promovierende der geistes-, kultur- und sozialwissenschaftlichen Fächer, die sich mit der Analyse sozialer Strukturen beschäftigen und Einblick in die Methoden der Sozialen Netzwerkanalyse (SNA) nehmen möchten. Auch Studierende, die kurz vor ihrer Diplom-/Master-/Magister­arbeit stehen und methodisch mit der SNA arbeiten wollen, sind willkommen.


Die Anmeldephase beginnt am Montag, 28. April und endet am Donnerstag, 31. Juli 2014.

Die Teilnehmerzahl ist auf 40 Teilnehmer begrenzt. Wenn Sie sich anmelden möchten, besuchen Sie bitte die Summer School Homepage ( Dort finden Sie unter „Anmeldung“ ein Anmeldeformular.

Da die Teilnehmerzahl auf insgesamt 40 Teilnehmer beschränkt ist, melden Sie sich bitte rechtzeitig an.

Die Teilnahmegebühr beträgt 290,00 Euro. Sie ist 21 Tage nach Erhalt der Anmeldebestätigung fällig. Die Anmeldung wird erst wirksam, wenn die Teilnahmegebühr auf dem in der Bestätigungsmail angegebenen Konto eingegangen ist. Zusammen mit der Bestätigung des Zahlungseingangs erhalten Sie weitere Informationen bzgl. Veranstaltungsort, Übernachtungsmöglichkeiten und Busanbindung. Ebenso wird Ihnen vorbereitende Literatur zu den Lehrveranstaltungen zur Verfügung gestellt. Auf der Homepage der Summer School können Sie sich ebenfalls informieren.

Aufbau der 8. Trierer Summer School

Modul 1: „Grundlagen der Sozialen Netzwerkanalyse“

Vom 29. bis 30. September führt das erste Modul ganztägig in die Geschichte und theoretische Konzepte sowie in Methoden der Datenerhebung, -auswertung und -visualisierung der SNA ein. Die Veranstaltung richtet sich an alle Teilnehmer, insbesondere aber an Anfänger, und bietet einen ersten Einstieg in die Thematik.

Die Lehreinheit ist als Vorlesung mit integrierten Übungen und Gruppenaufgaben strukturiert. Es werden sowohl ego-zentrierte Netzwerke als auch Gesamtnetzwerke behandelt. Unter egozentrierten Netzwerken werden Netzwerke verstanden, die sich um ein Ego (ein bestimmter Akteur/die befragte Person) positionieren. Bei der Gesamtnetzwerkanalyse steht hingegen eine ausgewählte Gruppe von Akteuren (Unternehmen, Schulklassen, Dörfer usw.) und die soziale Struktur innerhalb dieser Gruppe im Fokus.


Dr. Markus Gamper, Universität zu Köln

Dr. Richard Heidler, Bergische Universität Wuppertal

Dr. Andreas Herz, Universität Hildesheim

Modul 2: „Praxisorientierte Soziale Netzwerkanalyse“

Modul 2 (01.-04. Oktober) umfasst zwei parallel laufende Angebote zur Datenerhebung und -auswertung von Sozialen Netzwerken. Am Mittwoch, 01. Oktober, erfolgt das Modul ganztägig, von Donnerstag bis Samstag jeweils nur vormittags. Je nach Forschungsinteresse können die Teilnehmer zwischen zwei Arbeitsgruppen entscheiden:

Arbeitsgruppe A – Gesamtnetzwerke (20 Plätze):

Welches übergeordnete Strukturmuster hat ein Netzwerk? Wo befinden sich Bereiche verdichteter Kommunikation? Welche Akteure sind zentral, wer sind die Broker in einem Netzwerk? Welche strukturellen und attributionalen Faktoren beeinflussen die Entstehung, Beibehaltung und Beendigung von Relationen? Diese Fragen lassen sich mit Gesamtnetzwerken untersuchen. Im Unterschied zu ego-zentrierten Netzwerken wird hier nicht nur die direkte Umgebung eines Akteurs erfasst, sondern die Gesamtheit der Beziehungen, zwischen einem abgegrenzten Set von Akteuren, wie z. B. einer Schulklasse, einem Politikfeld, einer wissenschaftlichen Disziplin, einem Dorf, usw.

Das Modul Gesamtnetzwerke legt einen Schwerpunkt auf das Einlesen und das Auswerten von Daten von Gesamtnetzwerken. Dabei wird eine Bandbreite von Software zum Einsatz kommen, wodurch ihre unterschiedlichen Stärken und Schwächen aufgezeigt werden. Typische Netzwerkformate und Verfahren der Datenmodifikation, sowie die Berechnung von Zentralitätsmaßen werden mit Pajek durchgeführt. Auch die Blockmodellanalyse wird in Pajek zum Einsatz kommen, und dann in GNU-R fortgesetzt. Die Grundlagen von R werden in einer Sitzung die gemeinsam mit dem Egomodul stattfindet gelehrt. Darüber hinaus wird R verwendet, um Syntax-basiert Auswertungen und Transformationen von Netzwerken vorzunehmen. Schließlich wird in R auch die Modellierung von Netzwerken mit ERGM, anhand einer Schulklasse von 1880/81 demonstriert. Final kommt das Programm Gephi zum Einsatz, um sich besonders mit den Fragen und Anforderungen guter visueller Darstellungen von Netzwerken zu beschäftigen. Hierzu wird ein Hochzeitsnetzwerk grafisch repräsentiert. Das Format des Moduls umfasst praktische Übungen, Diskussionen und lässt auch Raum für eigene Vorschläge.

Dozenten: Dr. Richard Heidler / Michael Kronenwett, M. A. (Kronenwett & Adolphs UG)

Arbeitsgruppe B – Ego-Netzwerke (20 Plätze):

Welche Formen sozialer Unterstützung werden von verschiedenen Beziehungen erbracht? Hat die Einbettung eines Akteurs in sein soziales Netzwerk Auswirkung auf die Generierung innovativer Ideen oder führt Mediennutzung zu Desintegration? All diese Fragen lassen sich mit Verfahren der ego-zentrierten Netzwerkanalyse untersuchen, wobei ego-zentrierte Netzwerke formal die Beziehungen eines Akteurs (Ego) zu anderen Akteuren (Alteri) dessen direkter Netzwerkumgebung sowie den Beziehungen zwischen diesen Akteuren (Alter-Alter-Relationen) darstellen.

Das Modul „ego-zentrierte Netzwerke“ führt in offene und standardisierte Erhebungs- und Auswertungsverfahren ego-zentrierter Netzwerke ein. Nach einer exemplarisch durchgeführten Fragebogenerhebung und ausführlicher Diskussion von offenen und standardisierten Erhebungsvarianten, liegt der Fokus auf der quantitativen Auswertung eines bereits vorliegenden Datensatzes mit Hilfe GNU-R. Hierzu werden Daten- und Analyseebenen sowie grundlegende Analysestrategien verdeutlicht. Daneben werden auch qualitative Verfahren vorgestellt, die dann in den Nachmittags-Workshops nochmals vertieft werden können. Für die Teilnahme sind Grundkenntnisse in statistischer Datenanalyse von Vorteil. Je nach Bedarf und TeilnehmerInneninteresse werden Analysemöglichkeiten auch für qualitative Netzwerkkarten diskutiert. Das Format des Moduls umfasst Kurzeinführungen, praktische Übungen und Diskussionen.

Dozenten: Dr. Markus Gamper / Dr. Andreas Herz

An das Modul 1 schließt sich am Dienstagabend eine Fragerunde rund um das Modul 2 „Praxisorientierte Soziale Netzwerkanalyse“an. Die Teilnehmer haben hier die Möglichkeit, den Dozenten konkrete Fragen zu den Lehrinhalten der beiden Arbeitsgruppen A und B sowie den angebotenen zusätzlichen Workshops zu stellen. Auf der Grundlage der Kenntnisse aus Modul 1 kann die Entscheidung für die Teilnahme an einer Arbeitsgruppe noch einmal überdacht und bei Bedarf, soweit organisatorisch möglich, geändert werden.

Am Samstag (4.10.) findet parallel zu den Arbeitsgruppen „Gesamtnetzwerk“ und „Ego-Netzwerke“ die folgende Veranstaltung statt:

„Governance und soziale Netzwerke“

Das interaktive Modul Governance und soziale Netzwerke beschäftigt sich mit der Analyse qualitativer und quantitativer sozialer Netzwerkdaten zur Untersuchung von Governance-Prozessen. Behandelt werden unter anderem politische Entscheidungs- bzw. Implementierungsprozesse im Europäischen Mehrebenensystem, Akteursanalysen einschließlich Macht- und Einflussverteilung in Netzwerken, strategische Netzwerkplanung, soziales Lernen und Wissensintegration.

Dozentin: Dr. Jennifer Hauck (Helmholtz-Zentrum für Umweltforschung)

Keynote Speech: Network Analysis Literacy

Am Dienstag, den 30. September, hält Prof. Katharina Anna Zweig (University of Science and Technology Kaiserslautern) einen Keynote Speech mit dem Titel „Network Analysis Literacy“: Die Netzwerkanalyse bietet eine Reihe von etablierten Methoden, um beispielsweise die zentralsten Knoten zu finden, ein Netzwerk in dichte Teilbereiche zu partitionieren oder statistisch signifikante Teilgraphen zu identifizieren. Aber für jede dieser Aufgaben gibt es verschiedene Ansätze, sie zu lösen. So gibt es beispielsweise mehrere Dutzend Zentralitätsindizes. In diesem Vortrag geht es um die Frage, warum es so viele verschiedene Ansätze gibt und nach welchen Regeln man entscheiden kann, wann welcher Ansatz verwendet werden sollte. Dazu muss das „Trilemma der Analyse komplexer Netzwerke“ verstanden und gelöst werden. Anhand verschiedener Beispiele wird Prof. Zweig dessen Bedeutung darlegen und generelle Lösungansätze diskutieren.

Dozentin: Prof. Katharina Anna Zweig (University of Science and Technology Kaiserslautern)


Workshop „Prozessgenerierte Daten und historische Netzwerkanalyse“

Die Untersuchung von Netzwerkdynamiken, d. h. der Veränderung von Netzwerkstrukturen in der Zeit, gewinnt unter Historikern und Sozialwissenschaftlern eine immer größere Bedeutung. Hierbei ist es aber oftmals nicht möglich oder praktikabel, “klassische“ Formen der sozialwissenschaftlichen Datenerhebung wie Befragungen und Beobachtungen anzuwenden. Prozessgenerierte Quellen oder Daten liegen hingegen oftmals bereits für längere Zeiträume vor und ermöglichen vielfältige dynamische Analysen. Prozessgenerierte Quellen entstehen beispielsweise während Verwaltungsvorgängen aber auch während „Oral History Interviews“. Sie sind nicht direkt durch die Forschenden für individuelle Fragestellungen erhoben worden und müssen deshalb kundig und kritisch interpretiert werden um für aussagekräftige Datenerhebungen nutzbar zu werden. Ziel des Workshops ist es, eine Einführung und praktische Handreichung in die Besonderheiten der Erhebung von dynamischen Netzwerkdaten aus prozessgenerierten Quellen zu geben.

Der Workshop gliedert sich wie folgt: Grundlagen, Quellenübung, Dateneingabe/Codierung, Datenausgabe(Einstieg in die Auswertung)/Fragen und Diskussion.

Dozenten: Dr. Martin Stark (Universität Hamburg), Dr. Marten Düring (CVCE Luxemburg)

Workshop „Mixed Methods“/“Visual Network Research“

Der Workshop ist als eine Erweiterung des im Modul 1 angeschnittenen Zweigs der „qualitativen Netzwerkanalyse“ zu sehen. Im Nachmittagsprogramm werden am 2. und 3. Oktober in zunächst zwei parallel stattfindenden Übungen die beiden Tools VennMaker und NetMap, einschließlich der kombinierten Erhebung qualitativer und quantitativer Netzwerkdaten vorgestellt. Am zweiten Nachmittag werden gemeinsam mit allen Workshop-Teilnehmern die Grundlagen und Methoden der partizipativen und qualitativen Datenanalyse besprochen und Wege aufgezeigt, wie die unterschiedlichen Formen der Netzwerkanalyse miteinander verbunden werden können.

Die Teilnehmer können zwischen den folgenden zwei Übungen wählen:

A) VennMaker

Die Software „VennMaker“ steht an der Schnittstelle von qualitativer und quantitativer Netzwerkanalyse. Sie erlaubt Netzwerke per digitalem Fragebogen oder mithilfe digitaler Netzwerkkarten zuerheben, und beide Formen lassen sich auch miteinander kombinieren. Aufgrund seines visuellen Erhebungscharakters ist der VennMaker besonders gut für partizipative Netzwerkinterviews, bzw. Formen der kommunikativen Validierung geeignet. Die erhobenen Daten können in „klassischer Weise“ mit Excel, Pajek oder R quantitativ ausgewertet werden. Die zeitgleiche Aufzeichnung der gesprochenen Kommentare während des Interviews sowie die Einbindung von Textkommentaren etc. lassen aber auch eine qualitative Auswertung zu. In Gruppenarbeit wird das Erstellen von Netzwerkkarten mit Hilfe des VennMakers erlernt. Die praktische Übung sieht die Konfiguration, Durchführung sowie Auswertung eines Interviews vor. Des Weiteren wird die Migration der Daten in Officeanwendungen und R erprobt.

Dozent: Michael Kronenwett, M. A. (Kronenwett & Adolphs UG)

B) Net-Map

Das Net-Map-Tool ist eine interview-basierte Methode, die es erlaubt, das Wissen um Netzwerkstrukturen als Netzwerkkarte direkt mit Papier und Stift sichtbar zu machen. Darüber hinaus können, während des Interviewprozesses, vielfältige Daten zu den Akteuren und qualitative Informationen erhoben werden, welche die Rollen der Akteure und Netzwerkstrukturen besser verständlich machen. Während des Workshops erarbeiten die TeilnehmerInnen, nach einer kurzen Vorstellung des Net-Map-Tools, relevante Fragestellungen aus ihrem jeweiligen Forschungsbereich und lernen die Anwendung des NetMap-Tools anhand dieser Fragen. Anschließend werden verschiedene Möglichkeiten der Digitalisierung der Netzwerkkarten aufgezeigt und erste Auswertungsschritte besprochen.

Dozentin: Dr. Jennifer Hauck (Helmholtz-Zentrum für Umweltforschung)


Am 2. und 3. Oktober stehen die Dozenten den Teilnehmern für eine Forschungsberatung zur Verfügung. In einem persönlichen Gespräch können Lösungen für die eigenen Forschungsaufgaben und -projekte besprochen und gefunden werden. Die Teilnehmer profitieren hierbei von der Expertise und den Erfahrungen der Dozenten.

Das Angebot wurde aufgrund des großen Erfolges und der hohen Nachfrage der letzten Jahre wieder in das Programm aufgenommen. Wenn Sie das Angebot in Anspruch nehmen wollen, reichen Sie bitte bis zum 31. Juli ein Abstract (Details hierzu: siehe oben) ein.

Abschlussvortrag „Ethische Netzwerkforschung? Eine Sensibilisierungsrunde zum Abschluss“

Bei der Netzwerkforschung geht es um das Aufdecken von Beziehungen in Gruppen, die oft in hohem Maße informeller Natur und persönlich sind, wobei auch teils vertrauliche Informationen weitergegeben werden. Mit folgenden Fragen lassen sich ethische Aspekte in der Netzwerkforschung ganz gut überprüfen:

„Wer erhebt mit wessen Wissen und Zustimmung wessen Netzwerke, mit Hilfe welcher Quellen, mit welchem Ziel, zu wessen Nutzen, und mit welchen Folgen?“

Nachdem wir uns eine Woche lang gemeinsam dem `wie` und `was` der NWF nachgegangen sind, wollen wir die letzte gemeinsame Runde dazu nutzen, um Sie für das auf Netzwerktagungen bisher kaum thematisierte `warum` und `für wen` der NWA zu sensibilisieren, und mit Ihnen zu diskutieren.

Dozent: Prof. Dr. Michael Schönhuth (Universität Trier)


Neben dem Gastvortrag bietet das gesellige und kulturelle Rahmenprogramm der Summer School die Möglichkeit, das eigene „social networking“ zu betreiben. Beim geselligen Abend lernen sich die Teilnehmer näher kennen und bereits begonnene Gespräche können bei einem Glas Wein weiter vertieft werden. Ebenso wird die alte Römerstadt Trier mit ihren Sehenswürdigkeiten aus allen Jahrhunderten auf einer Stadtführung erkundet.

Problems with archaeological networks part 1

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

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

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

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

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

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

Prosopographies and social networks workshop

prosopProsopographies are great sources for building past social networks. Those interested in or working with large datasets of past individuals might be interested in the Prosop workshop. More information below. or on

Prosop: a social networking tool for the past

Call for participants

Second database development workshop

Florida State University (Tallahassee, FL) on May 9, 2014.

Historians and other scholars with large databases of historical person data are invited to a workshop to test and populate Prosop, a project funded by the Office of Digital Humanities of the National Endowment for the Humanities.

What is Prosop?

Prosop is a collaborative semantic web database of details about individuals in the past. Although it maps networks and discovers connections, it is not just facebook for dead people. In particular, it aims to:

  • manage diverse types of data from different historical settings,
  • aggregate of large quantities of person data,
  • accommodate uncertain and conflicting information, and
  • facilitate data-driven study of historical systems of description and classification.
  • For more detailed information, visit our website at

What kinds of data do we seek?

We’re looking for information about relatively large sets of relatively ordinary people from the past. Typically, this information is extracted from archival records used by microhistorians. For example, the database contains the name, age, address, and physical description of 700 criminal court defendants from 1880s Egypt. Prosop is meant to work for all kinds of historical person data, and we are especially interested in data in unusual formats (linguistic, topical, or otherwise) that will help us to develop the flexibility of the system. Also, we are looking for participants who are willing to share their data with the community of researchers using Prosop.

Applying with a counterpart

For this workshop, we are especially interested in applications from pairs of researchers who have similar datasets and would like to test them for possible overlap. Prosop may help them to discover common individuals and explore community characteristics.

What will happen at the workshops?

Before the workshop, each participant will submit a tranche of names, which will be imported into Prosop. Participants will describing the characteristics of their data and the ways it might interact with other person data. Those working in pairs will consider any overlap that Prosop found, as well as commonalities that it fails to discover. Participants will discuss issues of categorization and comparison that arise. We will work to find ways to link data and to make the system more usable. The workshop will provide a chance for historians and developers to communicate.

What’s in it for participants?

Workshop participants will contribute to the design of a tool that will enable new research into global social history, and will have early access to its results. They should gain new perspectives on their own data and its place in the global history of person information. Those working in pairs may discover fruitful overlap between their data sets. Participants’ experience and input will help to refine the system towards its aim, which is to encompass all categories of historical person data. Participant costs will be covered by the organizers, though some cost sharing may be asked of those applying from abroad.

How to apply?

Apply via the form available here. You will be asked to attach a CV and a letter of application, which should include a general description of the data which you wish to contribute to the project. Where possible, please specify:

  • the number of persons in the database
  • the categories of information recorded about each person (e.g. name, age, birthplace, occupation)
  • the geographical and chronological range of the persons represented
  • the type of sources from which the information is drawn (language, archives, genres).

What is the deadline for applications?

The deadline for applications for the second workshop is April 7, 2014.

Are there other ways to participate?

Prosop is an ongoing project. In addition to possible future workshops, we are looking for beta testers. If you are not able to join this workshop, but might want to be involved in the future, please get in touch via our website and join our mailing list.

Archaeology session at Sunbelt SNA conference

sunbeltThe Sunbelt series of conferences is the traditional venue for the Social Network Analysis community to showcase their new work. Last year it featured an archaeological session for the very first time, organised by Angus Mol and Ulrik Brandes. At this year’s Sunbelt there will again be an archaeological session, this time organised by Viviana Amati and Termeh Shafie. Let’s hope this will become a tradition! If you happen to be in Florida and have the time, drop by the sunbelt conference: 18-23 February in St. Pete Beach, Florida.

The line-up for this session sounds great. You can download the full schedule on the Sunbelt website. Here is the schedule for the archaeology session:

Friday 21 February, 8:40 – 10:20 AM, Blue Heron room

Emma Blake: Networks and ethnicities in early Italy

Jessica Munson: Sociopolitical networks and the transmission of ritual practices in Classic Maya society

John Roberts, Jr., Ronald Breiger, Matthew Peeples, Barbara Mills: Sampling Variability in Archaeological Network Measures

Jonathan Scholnick: Investigating cultural transmission among historic New England gravestone carvers with social network analysis

Mark Golitko: Procurement and distribution of obsidian in prehispanic Mesoamerica, 900 BC – AD 1520: an economic network analysis

CFP Historical Network Research at Sunbelt SNA conferece Florida

histnetAfter a successful session at the Hamburg Sunbelt SNA conference and their conference also in Hamburg, my colleagues at Historical Network Research are hosting another session at next year’s Sunbelt, this time in Florida! All details for their call for papers you can find below.

Call for papers “Historical Network Research” at the XXXIV. Sunbelt Conference, 18-23 February – St Pete Beach

The concepts and methods of social network analysis in historical research are recently being used not only as a mere metaphor but are increasingly applied in practice. In the last decades several studies in the social sciences proved that formal methods derived from social network analysis can be fruitfully applied to selected bodies of historical data as well. These studies however tend to be strongly influenced by concerns, standards of data processing, and, above all, epistemological paradigms that have their roots in the social sciences. Among historians, the term network has been used in a metaphorical sense alone for a long time. It was only recently that this has changed.

Following a total of five successful sessions on network analysis in the historical disciplines at Sunbelt 2013 in Hamburg, we invite papers which integrate social network analysis methods and historical research methods and reflect on the added value of their methodologies. Topics could cover (but are not limited to) network analyses of correspondences, social movements, kinship or economic systems in any historical period.

Submission will be closing on November 30. Please limit your abstract to 250 words and submit your abstract here. Please mention “Historical Network Research” as session title in the comment section of the abstract submission website.

For further information on the venue and conference registration see the conference website, for any questions regarding the panel, please get in touch with the session organizers.

Session organizers:
Marten During, Centre virtuel de la connaissance sur l’Europe,
Martin Stark, University of Hamburg,
Scott B. Weingart, Indiana University Bloomington,

Check historical networks research for a detailed bibliography, conferences, screencasts and other resources.

With best wishes,

Marten on behalf of Martin and Scott

The Future of Historical Network Research

histnetI am delighted to spread the word about a great upcoming conference: The Future of Historical Network Research. It is organised by the Historical network analysis team that have been holding regular workshops in Germany for a few years now. This is their first conference and I was told to expect an awesome keynote! The event will take place at the University of Hamburg on 13-15 September 2013. There are even a limited number of bursaries available.

Deadline of the CFP is 25 July 2013.

More info can be found on the conference website and below.

Call for Papers

The concepts and methods of social network analysis in historical research are no longer merely used as metaphors but are increasingly applied in practice. In the last decades several studies proved that formal methods derived from social network analysis can be fruitfully applied to selected bodies of historical data as well. This relational perspective on historical sources has helped historical research to gain an entirely new methodological vantage point. Historical Network Research today is a research method as well as an online and offline training framework and quickly growing research community.

We are grateful for generous support from:

NeDiMAH – Network for Digital Methods in the Arts and Humanities

ESF – European Science Foundation

CGG – Centrum for Globalisation and Governance at the University of Hamburg

When we began to apply network analysis to history, there were no suitable points of reference and hardly any previous work which successfully combined Social Network Analysis methods and source-criticism. Over the years we have developed an infrastructure for historians to engage in research on networks, to exchange ideas and to receive training.
After eight workshops on Historical Network Research at locations in Germany, Austria and Switzerland it is time to look back at what has been achieved in the last years and to explore what might be next. For this first conference we therefore invite papers which integrate social network analysis methods and theories with historical research interests. Topics can cover any historical epoch and may include but are not limited to research on the topics below. Contributions from scholars in Computer Science, the Digital Humanities and related disciplines are welcome.

Collective action
Trade networks
Credit networks
Covert networks
Spatial networks
Dynamic networks
Kinship networks
Tools for the extraction of relational data from text
Network extraction from metadata
Semantic networks
Tools for data visualisation and management
Communication networks
Transnational networks

The papers will be organized as parts of the following four panels:

Section I: “Information Visualisation”
Section II: “Space and Time”
Section III: “Linked Data and Ontological Methods”
Section IV: Overlaps between Network Analysis and the Digital Humanities

The conference will include keynotes by scholars in history, computational linguistics, semantic networks and data visualisation who will discuss their vision for the future of computer-assisted historical research.

Abstracts of no more than 250 words should be submitted via this registration form by 25 July 2013. Notifications of paper acceptance will be sent out by 5 August.

Please do not hesitate to contact us at for additional information.

Linda von Keyserlingk, Militärhistorisches Museum der Bundeswehr
Florian Kerschbaumer, University of Klagenfurt
Martin Stark, University of Hamburg
Ulrich Eumann, NS Dokumentationszentrum Köln
Marten Düring, Radboud University Nijmegen

Applications of Social Network Analysis (ASNA)

asnaThe Applications of Social Network Analysis conference might be of interest to some. Held in Zurich, 27-30 August 2013. The event combines paper sessions with hands-on practical workshops including SNA (advanced and newbie), Siena, Visone, ERGM in R, and Discourse. The workshop on Visone will be led by Ulrik Brandes ad Uwe Nagel, the University of Konstanz team you might know from the Caribbean Archaeology project Nexus 1492.

More info can be found on the ASNA website.

SNA Summer School Trier

Image from University Trier website.
Image from University Trier website.
Dear German-speaking friends (and everyone who likes the sound of the German language)! The University of Trier will organise a summer school in Social Network Analysis on 23-28 September 2013. My friends Marten Düring and Martin Stark, both historians, will be instructors at the Summer School. The school offers a one-week intense course in SNA, papers, workshops and software sessions. Sounds good? Sign up!

More info can be found on the Trier website and below.

Trie­rer Sum­mer School on So­ci­al Net­work Ana­ly­sis
23.-28. Sep­tem­ber 2013

Die Trie­rer Sum­mer School on So­ci­al Net­work Ana­ly­sis bie­tet im Rah­men eines ein­wö­chi­gen In­ten­siv­an­ge­bots eine um­fas­sen­de Ein­füh­rung in die theo­re­ti­schen Kon­zep­te, Me­tho­den und An­wen­dun­gen der So­zia­len Netz­werkana­ly­se. Die Ver­an­stal­tung rich­tet sich an Nach­wuchs­wis­sen­schaft­le­rIn­nen und Stu­die­ren­de aller geis­tes-, kul­tur- und so­zi­al­wis­sen­schaft­li­chen Fä­cher, die sich mit der Ana­ly­se so­zia­ler Struk­tu­ren be­schäf­ti­gen und Ein­blick in die Me­tho­den der So­zia­len Netz­werkana­ly­se (SNA) neh­men möch­ten.

Das An­ge­bot auf einem Blick

eine Woche in­ten­si­ve Ein­füh­rung in die SNA durch Ex­per­ten
in­di­vi­du­el­le For­schungs­be­ra­tung durch die Do­zen­ten
ein­füh­ren­de Li­te­ra­tur im On­line-Ap­pa­rat sowie Lern­ma­te­ria­li­en
Ein­füh­rung in gän­gi­ge Soft­ware zur SNA (Pajek, Gephi)
Gast­vor­trag: Mi­ri­am J. Lub­bers (Uni­ver­si­tat Autònoma de Bar­ce­lo­na) „The dy­na­mics of per­so­nal net­works of im­mi­grants over an eight-ye­ar pe­ri­od“
Work­shop „Mixed Me­thods“/„Vi­su­al Net­work Re­se­arch“ (Net-Map, Venn­Ma­ker)
Work­shop „Data Mi­ning und an­ge­wand­te Netz­werkana­ly­se“
Work­shop „Pro­zess­ge­ne­rier­te Daten und his­to­ri­sche Netz­werkana­ly­se“
An­rech­nung der Sum­mer School nach ECTS mit 3 credit points
Ver­pfle­gung mit Snacks und Ge­trän­ken wäh­rend der Ver­an­stal­tung
an­ge­neh­me Ler­n­at­mo­sphä­re mit vie­len Ge­le­gen­hei­ten für “so­ci­al net­wor­king”
abend­li­ches Rah­men­pro­gramm (ge­mein­sa­mes Abend­es­sen/Stadt­rund­gang)

SNA in Mathematica 9

social-network-analysisThe new version 9 of Wolfram’s Mathematica includes a set of quite diverse social network analysis functions. They include a range of import formats (including Pajek, GXL and GraphML) to load your own data, but you can also extract data from social media platforms like Twitter and Facebook. Networks can be visualised and different lay-out algorithms can be used. It also includes a range of analysis techniques like communities, centrality, cliques and homophily. In addition, scale-free networks can be simulated.

I have not yet tried the software myself, so a full review is still pending. At first sight the combination of these functions makes Mathematica 9 look quite comprehensive for SNA. But there is no indication that its analytical capabilities are as exhaustive as Pajek or that its import/export formats are as flexible as UCINET. Other alternatives with a nice graphical user interface like Cytoscape and Gephi also include most of the features of Mathematica 9, although maybe the latter works faster than the other two? I believe the biggest strength might be that these SNA tools are integrated in a large mathematical program with diverse functionality, which might allow for pushing SNA results further.

Feel free to comment if you have experience with Mathematica. Would love to hear about how good this is.

Étudier les réseaux sociaux, SNA summer school in France

When I tell people that I specialise in archaeological computing they always think I am locked up in a cellar with a massive computer screen doing things other people don’t understand. They do not associate us with doing fieldwork in a sunny place, or digging up treasures. To some extent this is true: I am generally confronted with blank stares when I try to explain my research and I do get to sit in a warm and dry office whilst others excavate ridges and furrows in a muddy trench.

Sometimes being an academic is not such a bad thing. A few weeks ago I had the pleasure of being invited by a French historian to attend and present at a summer school. The week-long event took place on the French island of Proquerolles off the coast of Toulon and St Tropez, a little known gem of the French Riviera. When I did my background research before accepting the invitation I focused on weather forecasts and restaurant reviews. I decided it was in the best interest of my research group that I accept the invitation and attend this undoubtedly very interesting event.

A useful fact about Porquerolles is that it lies in France, where people speak French. The last time I practiced my French was quite a while ago and everyone I met after getting off the plane was keen to point that out to me. On the boat trip to the island I found out that in fact I was one of the only foreigners and one of only two archaeologists, all other 78 delegates were mainly sociologists, a few historians and some geographers. All of a sudden I very briefly wished I could spend the week in a cellar in front of a massive computer screen.

It turns out that the average French sociologist makes for extremely enjoyable and interesting company, although there are some distinct differences with the average archaeologist: they talk about sociology a lot and they drink less. The summer school (‘Etudier les réseaux sociaux’) was organised by the French social network analysts Claire Bidart and Michel Grosetti, and the historical network analysts Claire Lemercier and Michel Bertrand. The programme included some great scholars in social network analysis like Alain Degenne, Pierre Mercklé and Emmanuel Lazega. The topics of the presentations ranged from ‘Network Analysis for Dummies’, over the issues surrounding the use of historical data in network analyses, to networks of organisations, citations, finance and the World Wide Web. The work by Florent Hautefeuille on linking networks of individuals known from Medieval written sources with the excavated houses in which they lived was particularly interesting for archaeologists. One of the biggest strengths of the summer school were the many tutorials that introduced an impressive range of social network analysis software: Pajek, PNet, ERGM, NodeXL, Visone, Calliope, SIENA, UCINET, Netdraw, Gephi, as well as some more obscure programmes designed by individuals sitting in front of massive screens in cellars.

During a conference or summer school it is always hard to convince yourself that you are actually there for work and should stay focused during every second of all presentation. But at this summer school I came very close to paying attention almost non-stop to all the amazing new network techniques, software and their creative applications to fascinating datasets. I believe I should conclude by stating that I have seen the value of sharing knowledge across disciplines in action, especially if it takes place on a beautiful French island in the Mediterranean.

Historical network research on the web!

I just discovered the work by Marten Düring and his colleagues on Historical network research. They established a platform for scholars to discuss their network-related work and advertise events. Their website also includes a bibliography listing many historical applications of network-based techniques. In addition, some workshops are organised, the next one taking place 26-28 May in Saarbrücken, Germany. Definitely of interest to people reading this blog!

Here is what these scholars have to say about the scope of the platform:

This website aims to be a platform for scholars to present their work, enable collaboration and provide those new to network analysis with some helpful first information.

The concepts and methods of social network analysis in historical research are recently being used not only as a mere metaphor but are increasingly applied in practice. In the last decades several studies in the social sciences proved that formal methods derived from social network analysis can be fruitfully applied to selected bodies of historical data as well. These studies however tend to be strongly influenced by concerns, standards of data processing, and, above all, epistemological paradigms that have their roots in the social sciences. Among historians, the term network has been used in a metaphorical sense alone for a long time. It was only recently that this has changed.

The social sciences with their focus on the present-day have a vast range of tools at their disposal, such as interviews or questionnaires, to obtain data that are both informative and comprehensive. Historical research however is limited to the extraction of relational data from fragmentary and contradicting sources. Alongside with the paucity of sources this hampers the comprehensive, valid and meaningful application of methods drawn from social network analysis. Despite these obstacles, the relational perspective of network analysis has helped historical research to gain an entirely new methodological vantage point.

Historical research has faced up to the challenge posed by social network analysis. The latter has emerged as a young and dynamic field in historical research; it is still in its formative phase and as a consequence hard to view as a whole. Until now however, social network analysis methods and theories have been applied to historical data in various fields, for example in the study of correspondences, of social movements, of kinship and in economic history. The fragmentary nature of their sources often leads scholars to rely on rather robust concepts of centrality measures, bimodal networks, visualizations and the adaptation of widespread theorems such as brokerage or the concept of strong and weak ties.

CAA2011 networks session summary and discussion

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Leif Isaksen: how has the grave depth been recorded?

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Maximilian Schich: are you sure?

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

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

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

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

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

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

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

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

Social networks and genomes join forces

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

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

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

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

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

ego-networks on LinkedIn and Facebook

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

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

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

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

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