Data mining in the social sciences and iterative attribute elimination

Anthony Scime, Gregg R. Murray, Wan Huang, Carol Brownstein-Evans

Research output: Chapter in Book/Report/Conference proceedingChapter

4 Citations (Scopus)

Abstract

Immense public resources are expended to collect large stores of social data, but often these data are under-examined thereby missing potential opportunities to shed light on some of society's pressing problems. This chapter proposes and demonstrates data mining in general and an iterative attribute-elimination process in particular as important analytical tools to exploit more fully these important data from the social sciences. We use an iterative domain-expert and data mining process to identify attributes that are useful for addressing distinct and nontrivial research issues in social science-presidential vote choice and living arrangement outcomes for maltreated children-using the American National Election Studies (ANES) from political science and the National Survey on Child and Adolescent Well-Being (NSCAW) from social work. We conclude that data mining is useful for more fully exploiting important but under-evaluated data collections for the purpose of addressing some important questions in the social sciences.

Original languageEnglish (US)
Title of host publicationData Mining and Knowledge Discovery Technologies
PublisherIGI Global
Pages308-332
Number of pages25
ISBN (Print)9781599049601
DOIs
StatePublished - Dec 1 2008

Fingerprint

social science
social data
election research
life situation
political science
voter
social work
well-being
expert
adolescent
society
resources

ASJC Scopus subject areas

  • Social Sciences(all)

Cite this

Scime, A., Murray, G. R., Huang, W., & Brownstein-Evans, C. (2008). Data mining in the social sciences and iterative attribute elimination. In Data Mining and Knowledge Discovery Technologies (pp. 308-332). IGI Global. https://doi.org/10.4018/978-1-59904-960-1.ch013

Data mining in the social sciences and iterative attribute elimination. / Scime, Anthony; Murray, Gregg R.; Huang, Wan; Brownstein-Evans, Carol.

Data Mining and Knowledge Discovery Technologies. IGI Global, 2008. p. 308-332.

Research output: Chapter in Book/Report/Conference proceedingChapter

Scime, A, Murray, GR, Huang, W & Brownstein-Evans, C 2008, Data mining in the social sciences and iterative attribute elimination. in Data Mining and Knowledge Discovery Technologies. IGI Global, pp. 308-332. https://doi.org/10.4018/978-1-59904-960-1.ch013
Scime A, Murray GR, Huang W, Brownstein-Evans C. Data mining in the social sciences and iterative attribute elimination. In Data Mining and Knowledge Discovery Technologies. IGI Global. 2008. p. 308-332 https://doi.org/10.4018/978-1-59904-960-1.ch013
Scime, Anthony ; Murray, Gregg R. ; Huang, Wan ; Brownstein-Evans, Carol. / Data mining in the social sciences and iterative attribute elimination. Data Mining and Knowledge Discovery Technologies. IGI Global, 2008. pp. 308-332
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