A Network Approach to Pattern Discovery in Spell DataSean M. Fitzhugh, Carter T. Butts, Joy E. PixleyDepartment of Sociology, University of California-Irvine

MotivationThe goal is to identify population-level pat-terns using a network framework for represent-ing actors’ participation in multiple, simultane-ous spells. This framework relies on Butts andPixley’s (2004) structural representation of lifehistory data and simple life history graphs.1

How can we use spell data and a handful of covari-ates to discover activity patterns in a population?

Data

I use retrospective life history data from CharlesHirschman and his colleagues’ 1991 Vietnam LifeHistory Survey.2 Respondents listed the start andend dates of several spells, including schooling, work-ing, marriage, childcare, and military participation.

How Does the Method Work?

Use spell overlaps to construct interval graphsand convert them into networks. Find the dis-tance between all these interval graphs. Performa cluster analysis and look for patterns (actorsclose together have similar life histories). Morespell types allows for greater differentiation andconsequently more precise results, an improvementover a limitation of sequence analysis methods.4

SchoolSchool

SchoolWork

Work

Marriage

Children

Children

S S S W W M C C

S 1 0 0 0 0 0 0 0

S 0 1 0 0 0 0 0 0

S 0 0 1 0 0 1 0 0

W 0 0 0 1 0 1 1 0

W 0 0 0 0 1 1 1 1

M 0 0 1 1 1 1 1 1

C 0 0 0 1 1 1 1 1

C 0 0 0 0 1 1 1 1

Why Interval Graphs?The life course approach studies spells which areextensive in time.3 The context in which theseevents takes place is meaningful—spell overlapsprovide a useful representation of this context.1

Exploring the Data

Factors that Differentiate LifeHistories

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01234−67−910−13

Can Tho, Tien Tien,Hai Hung,Hai Duong,Long Hoa

Factors that Do Not SubstantiallyDifferentiate Life Histories

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0 50 100 150 200

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1920s1930s1940s1950s1960s1970s

Initial Findings

•Lives are most differentiated by childcare spells.•Location differentiates individuals’ life historiesthroughout their entire lives. Location is alsoassociated with differences in job industry,religion, and ethnicity.

•Gender, education level, and decade of birth areless important in differentiating life histories.

Further ApplicationsUsing after action reports such as the OklahomaCity Bombing Final Report5, we can examine:•Co-participation in activities (evacuation,search and rescue, triage) to anticipatetie-formation and future collaboration amongorganizations.

•Activity patterns of organizations involved oruninvolved with tasks on the critical path, asidentified by Program Evaluation ReviewTechnique (PERT).

Path DependencyWe can examine whether these clusters convergeor diverge over time and trace the paths actorsfollow en route to their final position.

T1 T2 T3 T4

Path Dependency Example

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Military Participation vs. No Military Participation

References

[1] Butts, Carter T. and Pixley, Joy E. (2004). "A Structural Approachto the Representation of Life History Data." Journal of MathematicalSociology, 28(2), 81-124.

[2] Hirschman, et al. (1991). Vietnam Life History Survey[3] Elder, Jr., G. H. (1995). The Life Course Paradigm: Social Change

and Individual Development. In Moen, P. and Luscher, K., (eds.)Examining Lives in Context: Perspectives on the Ecology of HumanDevelopment, (pp. 101-139). Washington, DC: AmericanPsychological Association.

[4] Abbot, Andrew and Forrest, John.(1986). "Optimal MatchingMethods for Historical Sequences" Journal of InterdisciplinaryHistory, Vol. 16, No. 3, 471-494

[5] Final Report: Alfred P. Murrah Federal Building Bombing April 19,1995. (1996). Stillwater, OK: Department of Central Services CentralPrinting Division.

NCASD

NETWORKS, COMPUTATION, and SOCIAL DYNAMICS

This material is based on research supported by the Officeof Naval Research under award N00014-08-1-1015