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Big Data and Research Opportunities Using HRAF Databases

Fischer, Michael D. and Ember, Carol (2018) Big Data and Research Opportunities Using HRAF Databases. In: Chen, Shu-Heng, ed. Big Data in Computational Social Science and Humanities. Computational Social Sciences . Springer. E-ISBN 978-3-319-95465-3. (doi:10.1007/978-3-319-95465-3) (KAR id:63909)

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http://dx.doi.org/10.1007/978-3-319-95465-3

Abstract

The HRAF databases, eHRAF World Cultures and eHRAF Archaeology, each containing large corpora of curated text subject-indexed at the paragraph-level by anthropologists, were designed to facilitate rapid retrieval of information. The texts describe social and cultural life in past and present societies around the world. As of the spring of 2017, eHRAF contains almost 3 million indexed “paragraph” units from over 8,000 documents describing over 400 societies and archaeological traditions. This chapter first discusses concrete problems of scale resulting from large numbers of complex elements retrieved by any given search. Second, we discuss potential and partial solutions that resolve these problems to advance research, whether based on specific hypotheses, classification or identifying and evaluating embedded patterns of relationships. Third, we discuss new kinds of research possibilities that can be further advanced, have not yet been successfully attempted, or have not even been considered using anthropological data because of scale and complexity of achieving a result.

Item Type: Book section
DOI/Identification number: 10.1007/978-3-319-95465-3
Uncontrolled keywords: Human Relations Area Files, HRAF, Anthropology, Archaeology, Information Technology, databases
Subjects: H Social Sciences
H Social Sciences > H Social Sciences (General)
Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Division of Human and Social Sciences > School of Anthropology and Conservation
Depositing User: Michael Fischer
Date Deposited: 09 Oct 2017 11:27 UTC
Last Modified: 16 Feb 2021 13:49 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/63909 (The current URI for this page, for reference purposes)
Fischer, Michael D.: https://orcid.org/0000-0003-4553-8624
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