networked history of institutions
DESCRIPTION
While “big data” allow researchers to capture detailed accounts of social behavior, generalized inference from these data are fundamentally limited by temporal censoring. “Long data” gleaned from historical archives capture patterns of behavior going back decades or centuries and allow us to analyze the evolution of institutions that have shaped and been shaped by major historical events. Organizations publish annual records like historical directories going back centuries that contain rich relational data about affiliations and appointments about populations with well-defined boundaries. Using data from the Biographical Directory of the United States Congress and Annuario Pontificio of the Roman Catholic Church, we identify a variety of interactions related to co-location, affiliation, and relationships for two influential institutions going back to the late eighteenth century. We identify regularities in the structures of these networks across time and compare changes in these networks as they react to major events such as wars and long-term historical trends such as industrialization and globalization. Our findings have implications for prevailing historical and sociological interpretations of social structure as well as for forecasting changes to these influential institutions.TRANSCRIPT
Building the Iron Cage: Evolution of Multidimensional Networks in the U.S. Congress and Catholic Hierarchy!
Brian Keegan (@bkeegan)!Sasha Goodman!Ryan Kennedy!David Lazer!!NetSci 2013!Copenhagen, Denmark!June 5, 2013!
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What is the “iron cage”?!• Max Weber’s “The Protestant
Ethic and the Spirit of Capitalism” (1905)!
• Social action based on efficiency and rationalism displaces social action based on tradition and lineage!
• Bureaucracy leads to:!• loss of autonomy!• centralized control!• specialization!
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Historical network analysis!• Arbesman (2013): “Long” data more important
than “big” data:!• The “real” social Pre-Cambrian era, not 2005!• 1k records x 1k events >> 1m records x 1 event!
• Padgett’s 15th century Florentine families (1993)!• Bearman’s 17th century Norfolk elites (1993)!• Gould’s 19th century Parisian neighborhood
networks (1995)!
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Research agenda!• Human mobility!
• Birth, education, appointment, death records!
• Affiliation!• Education, occupation, office records!
• Prediction!• Links, affiliations, promotions!
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Durable elite institutions!• United States Congress!
• National legislative body of world’s largest economy and most powerful military since early 20th century!
• Biographical data on members from since 1774!!
• Roman Catholic Church!• Senior leadership of largest Christian sect and
central institution of Western civilization since 5th century!
• Reliable biographical data on elite membership since 1760s!
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Benefits of elite institutions!• Bounded populations à fewer sampling biases!
• Detailed records!• “What features of elite trajectories predict promotion?”!• “How have the demographics of elites changed?”!!
• Influences and influenced by historical events!• “How has technology changed mobility patterns?”!• “How did revolutions influence leadership?”!
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Data – U.S. Congress!• Biographical Directory of the U.S. Congress!
• Office of the Historian of the U.S. Senate!• 11,390 members!• Birthplace, education, occupations, prior offices,
deathplace!
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Elite migration:Birth to Representation!
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Nodes: Sized by out-degree, colored by in-degree Edges: Sized by weight, colored by birth state
Elite migration:Birth to Death!
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Nodes: Sized by out-degree, colored by in-degree Edges: Sized by weight, colored by death state
Changes in mobility!
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Changing state “trade balances”!
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Data – Catholic Hierarchy!• Catholic-Hierarchy.org!
• David Cheney parsing Annuario Pontifico, Vatican Information Service, other publications since 2003!
• 33,940 records for Bishops & Cardinals to 15th Century, records more reliable after mid-17th Century!
• Birthplace, consectration, consectrator, appointments!
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Consecreations as social networks!
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2013 Papal Enclave!
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Predicting Pope Francis?!
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Discussion!• Historical archives encode a variety of relational, spatial,
and temporal data!• Mobility patterns!• Social relationships!• Affiliations with institutions!
• Training predictive models of electoral success, leadership & promotion based on “long data”!
• Estimate statistical models accounting for overlapping ties and longitudinal data to predict tie formation!
• Compare effects of same events (e.g., wars, technologies) on different institutions!
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Discussion!• Coordination and organization governed by:!
• Organic and informal systems mediated by distributed networks?!• Bureaucratic and formalized systems with formalized
relationships? (Powell 1990, Jones, et al. 1997)!
• “Long data” generally only captures formalized relationships – but these demonstrate substantial complexity, heterogeneity, dynamicism!
• Network theories of exchange, diffusion, closure, resource dependency allow us to potentially revisit historical accounts of institutional change and power!
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