Visualizing Union County: Proposed Guidelines for Network Visualization in Qualitative Social History

Friday, January 4, 2013: 8:30 AM
Rhythms Ballroom 2 (Sheraton New Orleans)
Elaine Frantz Parsons, Duquesne University
Network analysis has the potential to uncover more of the lived experiences of people whose lives are recorded only in occasional brief mentions. The extant data on most historical figures is frequently relational: census records reveal family and neighborly ties, vital records family ties, probate records family and friendship ties, membership rolls of churches, societies, and unions, and lists of names on petitions, or payrolls, ties of affiliation. Network Analysis aggregates this scanty data, breaks it into comprehensible slices, and generates various visual representations of it. This allows historians to construct meaningful historical accounts from it either quantitatively (assessing the changing qualities of a network over time, or the changing position and characteristics of individuals within it) or qualitatively, by visually exploring the structure of social relations to discover patterns not apparent from unaided textual research. Though new tools substantially lower the technical barriers to creating a network visualization, historians make several crucial choices in deciding which tools to use, which data to display, how to arrange it, and what to emphasize and deemphasize.

This paper uses my work in creating network representations of a criminal/victim map of Union County, South Carolina to illustrate key issues facing social historians turning archival data into network visualizations, then proposes a set of guidelines relating to:

  1. The extent to which a historian has an obligation to understand the logic behind the automated visualization system s/he adopts;
  2. The ways in which a historian should inform readers of how s/he has manipulated the network in order to make it visually comprehensible;
  3. The methods of manipulating network visualizations that are appropriate, and those that are not;
  4. Whether and how a historian should represent data which is ambiguous or uncertain.
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