Social Network Analysisin Historical Research

Claire Lemercier

National Center for Scientific ResearchCenter for the Sociology of Organizations

(CNRS-Sciences Po, Paris)

KULeuven, 21 September 2012

Social Network Analysisin Historical Research

• Doesn't exist? (in network terms)(but Redes, 2011,

Österreichische Zeitschrift für Geschichtswissenschaften, 2012, The Connected Past, etc.)

Social Network Analysisin Historical Research

• Doesn't exist? (in network terms)• What is historical research?

– That thing that historians do?– Research based on traces?– Longitudinal research?

Outline

1. Network? Analysis? What is it all about?2. Sources – What can be/has been done3. Time – What should be done4. Data and Software – How do I do it?

1. What is Social Network Analysis?

• A strong research tradition (with handbooks)• Not a school/theory

but not only a set of techniques/softwarea way to look at reality (a lens?)

• Not the only way to talk about networks/social ties

– cf. physicists, etc.– cf. "normal" historians

1. What sort of network? What sort of analysis?

• "Networks": a way to view things, not a separate type of things

• A network is not a group(but a set of ties and non-ties between entities)

1. What sort of network? What sort of analysis?

• "Networks": a way to view things• A network is not a group• There is no such thing as

"the network of an individual"(nothing we can "map", anyway)

1. What sort of network? What sort of analysis?

• "Networks": a way to view things• A network is not a group• There is no such thing as

"the network of an individual"• Software does not find networks in sources

you have to find them, and thus first to define ties that will be systematically recorded, i.e. abstracted

1. What sort of network? What sort of analysis?

• "Networks": a way to view things• A network is not a group• There is no such thing as

"the network of an individual"• Software does not find networks in sources• "To analyze" a network

=to find a structure/patternsat different scales

11

Some networks do not need much analysis...

… Others do

Lemercier, 2005

1. Why bother?• A fresh look at things• Find structure in a mess

borders! hierarchies!structure is created by

absent ties

1. Why bother?

• A fresh look at things• Find structure in a mess• Discuss ties

in a more symmetrical/systematic waydo the successful have many ties?do ties explain success?

1. Why bother?

• A fresh look at things• Find structure in a mess• Discuss ties

in a more symmetrical/systematic way• Test hypotheses

what do ties do? cf. Padgett and the Medici(but sometimes, ties do not do much – e.g. Fertig)

1. Why bother?

• A fresh look at things• Find structure in a mess• Discuss ties

in a more symmetrical/systematic way• Test hypotheses

what do ties do?where do ties come from?cf. Padgett and the Medici, part 2

1. Why bother?

• A fresh look at things• Find structure in a mess• Discuss ties

in a more symmetrical/systematic way• Test hypotheses• Graphs for exploration/communication,

indicators/statistics for tests

1. Thinking about ties

• Not "Is there a network here?" (there always is)

1. Thinking about ties

• Not "Is there a network here?" (there always is)• But: when looking for ties in sources:

– What is this tie? Who says so?– Is it a river or a riverbed (interaction vs. potential)?– Is it strong? In which ways?– When did it appear? When did it disappear?– Did actors consciously build/maintain/break it?

1. Thinking about ties

• Not "Is there a network here?" (there always is)• But: when looking for ties in sources (...)• And when interpreting results of network analysis:

– Is this tie/structure enabling and/or constraining?– What might local patterns (e.g. structural holes)

mean for this tie?

1. Thinking about ties

• Not "Is there a network here?" (there always is)• But: when looking for ties in sources (...)• And when interpreting results of network analysis:

– Is this tie/structure enabling and/or constraining?– What might local patterns (e.g. structural holes)

mean for this sort of tie?– How do different sorts of ties overlap/interact?– How do they interact with attributes of actors?

2. Networks from historical sources

• No scarcity of sources!

2. Networks from historical sources

• No scarcity of sources!• … well, it depends...• Not only ties between people

– Ties between places, words, artefacts, organizations...

– "2-mode networks", e.g. affiliationsperson-organization→ person-person→ organization-organization

Traces of interaction

Pierre Gervais, transcript of Gradis accounts

Armement du Navire La Renommée Dt a Divers £ 14188.3.6 Pour Le montant du dit armement non Compris 745 debitées cy devant lesquelles Jointes a cette Some de £ 14188.3.6 font £ 14933.3.6 debités cy Contre p la totalité du dt Armement Sçavoir à Caisse pour Journées & autres y Compris 2/m a l'Equipage £ 7858.15 à la Ve Coureau Forgeron 380.1 à Marchand pour quincaille 65.7(...)

Banchereau Dt a Chabbert & Banquet n/C £ 1416.13 p Sa traite Sur les dits pble a la fin d'Avril Suivant Sa Lettre du 19 courant

Mad d'Interville Dt; a Caisse £ 9.2 p fraix & droits de notre envoy d'une Caisse Liqueur & &

Pierre Gervais (in progress) from Gradis accounts

Networks from texts

Tilly, 1997

Düring 2012

Networks from lists

Düring 2012

Verbruggen 2007

Verbruggen 2007

Stuber & Krempel, forthcoming

Annuaire Desfossés, édition 1938

Thinking about sources...

3. The (historical) evolution/dynamics of networks

• Work in progress!• An atypical example: Isabelle Rosé's study of

Odon de Cluny

879

880

881

[...]

899

900

901

[...]

940

941

942

3. The (historical) evolution/dynamics of networks

• Work in progress!• An atypical example: Isabelle Rosé's study of

Odon de Cluny– An ego-network in the strong sense– Coding ties– Dating ties!

Do the oldest have more social capital?When do ties die?Do dead people have ties?

– Representing change: what do we move, what do we keep in place?

3. The (historical) evolution/dynamics of networks

• Work in progress!• An atypical example: Isabelle Rosé's study of

Odon de Cluny• Alternative strategies

– A time-scale

Sigrist & Widmer2011

3. The (historical) evolution/dynamics of networks

• Work in progress!• An atypical example: Isabelle Rosé's study of

Odon de Cluny• Alternative strategies

– A time scale(by the way, you can also project on a map...)

– A time scale with an innovative view of organizations

François, 2009

3. The (historical) evolution/dynamics of networks

• Work in progress!• An atypical example: Isabelle Rosé's study of

Odon de Cluny• Alternative strategies• Modeling (micro)dynamics,

not only describing change?"Siena" modeling (based on simulation)

Lemercier & Rosental, 2010

Changes from migration ca. 1860 to migration ca. 1880

Rate parameters: 0. Rate parameter 17.0456 ( 1.0511)Other parameters: 1. eval: outdegree (density) -1.8468 ( 0.1625) 2. eval: reciprocity 0.4143 ( 0.1180) 3. eval: transitive triplets 0.1041 ( 0.0143) 4. eval: 3-cycles -0.0895 ( 0.0426) 5. eval: betweenness -0.0951 ( 0.0183) 6. eval: same language 0.9669 ( 0.1304)

4. Data formats and software• Good news: generic, manageable data formats• Not-so-good news: a complex, evolving

software landscape(but you can do it!)

4. Data formats and software• Good news: generic, manageable data formats

Edgelists (lists of ties)

4. Data formats and software• Good news: generic, manageable data formats

Edgelists (lists of ties)Generally accompanied by an "attribute file"

4. Data formats and software• Good news: generic, manageable data formats

Edgelists (lists of ties)Generally accompanied by an "attribute file"Also works for "2-mode networks"

(software converts to 1-mode)

4. Data formats and software• Good news: generic, manageable data formats

Edgelists (lists of ties)Nodelists

one line per person, all his/her contacts on the lineor: list of members of the organization!

4. Data formats and software• Good news: generic, manageable data formats• Not-so-good news: a complex, evolving

software landscape– Zillions of possibilities (esp. visualization), often free– Communities to guide you

– Excel plugin, basic functionalities: NodeXL– Nice visualizations (but not-so-easy data entry?):

Visone– Very easy to use for beginners, great for visual

exploration of (not-too-big) data: Netdraw

4. Data formats and software• Not-so-good news: a complex, evolving

software landscape– Excel add-on, basic functions: NodeXL– Nice visualizations: Visone– Very easy to use for beginners: Netdraw– Classical SNA calculations:

Ucinet (non-free software - but cheap+community)– If you have larger networks (> 5000 "nodes"): Pajek– For modeling (and/or geeks):

assorted R packages (sna, igraph, statnet, RSiena...) / pnet

claire.lemercier@sciences-po.org

Historical Network Research website

The Networks Network